TRIP OPTIMIZATION SYSTEM AND METHOD FOR A TRAIN FIELD OF THE INVENTION The field Of invention relates to optimizing train operations, and more particularly to monitoring and controlling a train's operations to improve efficiency while satisfying schedule constraints. BACKGROUND Locomotives are complex systems with numerous subsystems, with each subsystem being interdependent on other subsystems. An operator is aboard a locomotive to insure the proper operation of the locomotive and its associated load of freight cars. In addition to insuring proper operations of the locomotive the operator also is responsible for determining operating speeds of the train and forces within the train that the locomotives are part of. 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 perscribeable operating speeds that may vary with the train location along the track. Moreover, the operator is also responsible for assuring in-train forces remain within acceptable limits. However, even with knowledge to assure safe operation, the operator cannot usually operate the locomotive so that the fuel consumption is minimized for each trip. For example, other factors that must be considered may include emission output, operator's environmental conditions like noise/vibration, a weighted combination of fuel consumption and emissions output, etc. This is difficult to do since, as an example, the size and loading of trains vary, locomotives and their fuel/emissions characteristics are different, and weather and traffic conditions vary. Operators could more effectively operate a train if they were provided with a means to determine the best way tti> drive the train on a given day to meet a required schedule (arrival time) while using the least fuel possible, despite sources of variability. BRIEF DESCRIPTION Embodiments of the invention disclose a system for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives. In an exemplary embodiment, the system comprises a locator element to determine a location of the train. A track characterization element to provide information about a track is also provided. The system also has a processor operable to receive information from the locator element, and the track characterizing element. An algorithm is also provided which is embodied within the processor having access to the information to create a trip plan that optimizes performance of the locomotive consist in accordance with one or more operational criteria for the train. An exemplary embodiment of the present invention also discloses a method for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives. The method comprises determining a location of the train on a track. The method also determines a characteristic of the track . The method further creates a trip plan based on the location of the train, the characteristic of the track, and the operating condition of the locomotive consist in accordance with at least one operational criteria for the train. An exemplary embodiment of the present invention also discloses a computer software code for operating a train having a computer processor and one or more locomotive consists with each locomotive consist comprising one or more locomotives. The computer software code comprises a software module for creating a trip plan based on the location of the train, the characteristic of the track, and the operating condition of the locomotive consist in accordance with at least one operational criteria for the train. An exemptary embodiment of the present invention further discloses a method for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives where a trip plan has been devised for the train. The method comprises determining a power setting for the locomotive consist based on the trip plan. The method also operates the locomotive consist at the power setting. Actual speed of the train, actual power setting of the locomotive consist, and/or a location of the train is collected. Actual speed of the train, actual power setting of the locomotive consist, and/or a location of the train is compared to the power setting. Another exemplary embodiment of the present invention further discloses a method for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives where a trip plan has been devised for the train based on assumed operating parameters for the train and/or the locomotive consist. The method comprises estimating train operating parameters and/or locomotive operating parameters. The method further comprises comparing the estimated train operating parameters and/or the locomotive consist operating parameters to the assumed train operating parameters and/or the locomotive consist operating parameters. Another exemplary embodiment of the present invention further discloses a method for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives where a trip plan has been devised for the train based on a desired parameter. The method comprises determining operational parameters of the train and/or the locomotive consist, determining a desired parameter based on determined operational parameters, and comparing the determined parameter to the operational parameters. If a difference exists from comparing the determined parameter to the operational parameters, the method further comprises adjusting the trip plan. An exemplary embodiment of the present invention further discloses a method for operating a rail system having one or more locomotive consists with each locomotive consist comprising one or more locomotives. The method comprises determining a location of the train on a track and determining a characteristic of the track. The method further comprises generating a driving plan for at least one of the locomotives based on tie locations of the rail system, the characteristic of the track, and/or the operating condition of the locomotive consist, in order to minimize fuel consumption by the rail system. Another exemplary embodiment of the present invention further discloses a method for operating a rail system having one or more locomotive consists with each locomotive consist comprising one or more locomotives. Towards this end the method comprises determining a location of the train on a track, and determining a characteristic of the track. The method further comprises providing propulsion control for the locomotive consist in order to minimize fuel consumption by the rail system. DRAWINGS A more particular description of examples 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, tike invention will be described and explained with additional specificity and detail through the use of the accompanying drawings in which: FIG. 1 depicts an exemplary illustration of a flow chart of an exemplary embodiment of the present invention; FIG. 2 depicts a simplified model of the train that may be employed; FIG. 3 depicts an exemplary embodiment of elements of an exemplary embodiment of the present invention; FIG. 4 depicts an exemplary embodiment of a fuel-use/travel time curve; FIG. 5 depicts an exemplary embodiment of segmentation decomposition for trip planning; FIG. 6 depjcts an exemplary embodiment of a segmentation example; FIG. 7 depicts an exemplary flow chart of an exemplary embodiment of the present invention; FIG. 8 depicts an exemplary illustration of a dynamic display for use by the operator; FIG. 9 depicts another exemplary illustration of a dynamic display for use by the operator; and FIG. 10 depicts another exemplary illustration of a dynamic display for use by the operator. DETAILED DESCRIPTION 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. Exemplary embodiments of the present invention solve the problems in the art by providing a system, method, and computer implemented method for determining and implementing a driving strategy of a train having a locomotive coasist determining an approach to monitor and control a train's operations to improve certain objective operating criteria parameter requirements while satisfying schedule and speed constraints. Throughout this disclose the term "present invention" or "invention" is used. Even through the term "exemplary embodiments)" does not immediately proceed the above cited term, the intent of "present invention" or "invention" is read to mean "exemplary embodiment(s) of the present invention." The present invention is also operable when the locomotive consist is in distributed power operations. 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. 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. Broadly speaking, the technical effect is determining and implementing a driving strategy of a train having a locomotive consist determining an approach to monitor and control a train's operations to improve certain objective operating criteria parameter requirements while satisfying schedule and speed constraints. To facilitate an understanding of the present invention, it is described hereinafter with reference to specific implementations thereof. The invention is described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract da(a types. For example, the software programs that underlie the invention can be coded in different languages, for use with different platforms. In the description that follows, examples of the invention are described in the context of a web portal that employs a web browser. It will be appreciated, however, that the principles that underlie the invention can be implemented with other types of computer software technologies as well. Moreover, those skilled in the art will appreciate that 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. 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. 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. The locomotives are connected together where no train cars are in between the locomotives. The train can have more than one consist in its composition. Specifically, there can be a lead consist, and more than one 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 consist is usually viewed as successive locomotives, those skilled in the art will readily recognize that a consist group of locomotives may also be recognized as a consist even when at least a car separates the locomotives, such as when the consist is configured for distributed power operation, wherein throttle and braking commands are relayed from the lead locomotive to the remote trails 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. Referring now to the drawings, embodiments of the present invention will be described. The invention can be implemented in numerous ways, including as a system (including a computer processing system), a method (including a computerised method), an apparatus, a computer readable medium, a computer program product, a graphical user interface, including a web portal, or a data structure tangibly fited in a computer readable memory. Several embodiments of the invention are discussed below. FIG. 1 depicts an exemplary illustration of a flow chart of the present invention. 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 (effective track grade and curvature as function of milepost 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. This data may be provided to the locomotive 42 in a number of ways, such as, but not t 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 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. The track signal system determines the allowable speed of the train. There are many types of track signal systems and the 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 the track is clear and the train may proceed at max allowable speed. They can also indicate 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). 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 locomotives. Other systems have wireless communications systems. Signal systems can also require the operator to visually inspect the signal and take the appropriate actions. The 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. Based on the specification data input into the present invention, 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 12. 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. 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 the profiles provides 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 preferred embodiment, instead of operating at the traditional discrete notch power settings, the present invention is able to select a continuous power setting determined as optimal for the profile selected. Thus, for example, if an optimal profile specifies a notch setting of 6.8, instead of operating at notch setting 7, the locomotive 42 can operate at 6.8. Allowing such intermediate power settings may bring additional efficiency benefits as described below. 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. 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 setup 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 setup, 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. Mathematically, the problem to be solved may be stated more precisely. The basic physics are expressed by: (Equation Removed) 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, 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 (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 setup 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 setup, 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: min fF(u(f))dt - Minimize total fuel consumption min Tf - Minimize Travel Time min Σu, +u1-1 )2 - Minimize notch jockeying (piecewise constant input) min [(du I dt)2dt - Minimize notch jockeying (continuous input) 4. Replace the fuel term F in (1) with a term corresponding to emissions production. A commonly used and representative objective function is thus (Equation Removed) The coefficients of the linear combination will depend on the importance (weight) given for each of the terms. Note that in equation (OP), u(t) is the optimizing variable which is the continuous notch position. If discrete notch is required, e.g. for older locomotives, the solution to equation (OP) would be discretized, which may result in less fuel saving. Finding a minimum time solution (a1 and a2 set to zero) is used to find a lower bound on, the preferred embodiment is to solve the equation (OP) for various values of Tf with 03 set to zero. 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: (Equation Removed) Where WH 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 present invention. Reference to emissions in the context of the present invention is actually directed towards cumulative emissions produced in the form of oxides of nitrogen (NOx), unbumed Hydrocarbons, and particulates. By design, every locomotive must be compliant to EPA standards for brake-specific emissions, and thus when emissions are optimized in the present invention this would be mission total emissions on which there is no specification today. At all times, operations would be compliant with federal EPA mandates. If a key 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. To solve the resulting optimization problem, in an exemplary embodiment the present invention transcribes a dynamic optimal control problem in the time domain 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 in an exemplary embodiment, suppose a train is traveling a 172-mile stretch of track in the southwest United States. Utilizing the present invention, an exemplary 7.6% saving in fuel used may be realized when comparing a trip determined and followed using the present invention versus an actual driver throttle/speed history where the trip was determined by an operator. The improved savings is realized because the optimization realized by using the present invention produces a driving strategy with both less drag loss and little or no braking loss compared to the trip plan of the operator. To make the optimization described above computationally tractable, a simplified model of the train may be employed, such as illustrated in FIG. 2 and the equations discussed above. A key refinement tc 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, leading 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 thermal and electrical limits on the locomotive and inter-car forces in the train. Referring back to FIG. 1, once the trip is started 12, power commands are generated 14 to put the plan in motion. Depending on the operational set-up of the present invention, one command is for the locomotive to follow the optimized power command 16 so as to achieve the optimal speed. The present invention obtains actual speed and power information from the locomotive consist of the train 18. Owing to the inevitable approximations hi 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. 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 fail in route, and errors in the initial database 63 or data entity 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. Other reasons a trip may be re-planned include directives from a remote location, such as dispatch and/or the operator requesting a change hi objectives to be consistent with more global movement planning objectives. More 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 failure 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. 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. The present invention 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. 4 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. 4 from many locomotives could use that information to better coordinate overall train movements to achieve a system-wide advantage in fuel use or throughput. 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 when a train is not on schedule for 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 tunes, 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 following a railroad company's desire for how such departures from plan should be handled or manually propose alternatives for the on-board operator and dispatcher to jointly decide the best way to get back on plan. Whenever a plan is updated but where the original objectives, such as but not limited to arrival time remain the same, additional changes may be factored hi concurrently, e.g. new feiture 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. A re-plan may also be made when it is desired to change the original objectives. Such re-planning can be done at either fixed preplanned tunes, manually at the discretion of the operator or dispatcher, or autonomously when predefined limits, such a 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 present invention can re-plan the trip to accommodate the delay at expense of increased fuel as described above or to alert the operator and dispatcher how much of the time can be made up a( all (i.e. 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 failure and/or equipment temporary malfunction (such as operating too hot or too cold), and/or detection of gross setup errors, such 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. 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 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 present invention wherein the present invention will recalculate the train's trip plan. The present invention 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 a scheduled meet and/or pass time constraint may not be met. As discussed herein, this is accomplished by trams transmitting data to the dispatch to prioritize how each fain should change its planning objective. A choice could depend either from schedule or fuel saving benefits, depending on the situation. For any of the manually or automatically initiated re-plans, the present invention may present mare than one trip plan to the operator. In an exemplary embodiment the present invention will present 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 hi FIG. 4. The present invention has the ability of learning and adapting to key changes in the train and power consist which can be incorporated either in the current plan and/or for 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. FIG. 3 depicts an exemplary embodiment of elements of the present 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 determine a location of the train 31. Examples of such other systems may 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 tachometers) 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. Information about travel locations may also be transferred from other trams. A track characterization element 33 to provide 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 consist 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 by other approaches 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. 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 radio frequency automatic equipment identification (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 present invention can adjust the operator interface to reflect the signaling system state at the givn 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. 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" timp objectives on the early part of a route may be employed as 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. As an exatople of the hedging strategy, if a trip is planned from New York to Chicago, die system may have an option to operate the train slower at either the beginning 0f the trip or at the middle of the trip or at the end of the trip. The present invention 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, track maintenance, etc., 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 present invention may also consider weighting/penalty as a function of time/distance into the future and/or based on known/past experience. Those skilled in the art will readily recognize that such planning and re-planning to take into consideration weather conditions, track conditions, other trains on the track, etc., may be taking into consideration at any time during the trip wherein the trip plan is adjust accordingly. FIG. 3 further discloses other elements that may be part of the present invention. A processor 44 is provided that is operable to receive information from the locator element 30, track characterizing element 33, and sensors 38. An algorithm 46 operates within the processor 44. The algorithm 46 is used to compute an optimized trip plan based on parameters involving the locomotive 42, train 31, track 34, and objectives ©f the mission as described above. 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 algorithm 46 has access to the information from the locator element 30, track characterizing element 33 and/or sensors 38 to create a trip plan minimizing fuel consumption of a locomotive consist 42, minimizing emissions of a locomotive consist 42, establishing a desired trip time, and/or ensuring proper crew operating time aboard the locomotive consist 42. In an exemplary embodiment, a driver, or controller element, 51 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 operating decisions autonomously. In another exemplary embodiment the operator may be involved with directing the train to follow the trip plan. A requirement of the present invention 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 way points. Though only a single algorithm 46 is discussed, those skilled in the art will readily recognize that more than one algorithm may be used where the algorithms may be connected together. The waypoint 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 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. In an exemplary embodiment, the present invention 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 Figure 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 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 3 segment trip is disclosed itt FIG. 6 and discussed below. Those skilled in the art will recognize however, tlrough segments are discussed, the trip plan may comprise a single segment representing the complete trip. FIG. 4 depicts an exemplary embodiment of a fuel-use/travel time curve. 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/tiavel-time curve 50 has to be re-computed for only the segment changed. This reduces time for having to recalculate 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 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. 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 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 one exemplary embodiment, a coaching mode the present invention displays information 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 is suggested operating conditions that the operator should use. In another exemplary embodiment, acceleration and maintaining a constant speed are performed by the present invention. However, when the train 31 must be slowed, the operator is responsible for applying a braking system 52. In another exemplary embodiment, the present invention commands power and braking as required to follow the desired speed-distance path. Feedback control strategies are used to provide corrections to the power control sequence in the profile to correct for such events 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 to assure 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. The present invention allows 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. As discussed herein, the present invention may employ a setup as illustrated in the exemplary flow chart depicted in FIG. 5, and as an exemplary 3 segment example depicted hi detail in FIGS. 6. As illustrated, the trip may be broken into two or more segments, Tl, T2, and T3. Though as discussed herein, 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 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 for an exemplary 3 segment 200 mile trip 97. Further illustrated are grade changes over the 200 mile trip 98. A combined chart 99 illustrating curves for each segment of the trip of fuel used over the travel time is also shown. Using the optimal control setup described previously, the present computation method can find the trip plan with specified travel time and initial and final speeds, so as to satisfy all tide 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, ftir example, in single-track operations where the time to be in or get by a siding is critical. The present invention finds a fuel-optimal trip from distance DO to DM, traveled in time T, with M-l intermediate stops at DI,...,DM-I, and with the arrival and departure times at these stops constrained by (Equation Removed) where tarr(D,), tdep(A)and A are the arrival, departure, and minimum stop time at the i* stop, respectively. Assuming that fuel-optimality implies minimizing stop time, therefore t^D,) = tarr(Dt) + Af, which eliminates the second inequality above. Suppose for each i=l,...,M, the fuel-optimal trip from DM to Dj for travel time t, Tmin (') < t>& MK (') ' *s known. Let F,(t) be the fuel-use corresponding to this trip. If the travel time from DJ.J to Dj is denoted Tj, then the arrival time at Dj is given by where Af0 is defined to be zero. The fuel-optimal trip from DO to DM for travel time T is then obtained by finding Tu i=l,. . . M, which minimize subject to 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 D,_t -' where fij (/(/,v<>y-_,,vtf) is the fuel-use for the optimal trip from DJJ.J to Dy, traveled in time t, with initial and final speeds of vy.i and vy. Furthermore, ty is the time in the optimal trip corresponding to distance Dy. By definition, ta - tm = T,. Since the train is stopped at DJO and DiN , vm = viH = 0. The above expression enables the function Fj(t) to be alternatively determined by first determining the functions /ff(•),!£j-£N,, then finding r0,l^j^N, and ve ,1 <; j < N,, which minimize subject to (Equation Removed) By choosing Dy (e.g., at speed restrictions or meeting points), v^ (/, f) - v^ (i, j) can be minimized, thus minimizing the domain over which fy() needs to be known. 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 Dv, 1 <: i <, M, 1 < j £ Nt?. At point Dy, the new optimal trip from Dy to DM can be determined by finding Tik ,j