Abstract:
A travel routing system, method and program product therefor. A location detector detects a current location. A geographical database provides details of a given area. Selecting a destination causes a route generator to generate routes through the area from the current location. A flood simulator receives meteorological data and determines flooding along the routes. A risk-modeling unit determines the risk to travelers of using each route. Before the risk-modeling unit is deployed, it is trained off-line to model travel risks using incidents in an incident data store and simulated flooding in the vicinity of the incidents.

Description:
BACKGROUND OF THE INVENTION 
       [0001]    1. Field of the Invention 
         [0002]    The present invention is related to systems and methods for routing travel and more particularly to flood aware systems and methods for routing travel. 
         [0003]    2. Background Description 
         [0004]    Flooded roads are hazardous and flooding has a large impact on traffic flow. Even standing water, when it is deep enough, may make roads impassable for normal land based transportation, e.g., bicycles, cars, buses, and trains, while floodwater two feet deep can float a car. A few inches of moving water can knock a person off her/his feet. Floodwater moving at two miles per hour (2 mph or about three kilometers per hour (3 kph)) can sweep a car off a road or bridge, and cause the car to roll, trapping the driver and passengers and making it difficult or impossible to escape. Moreover, the moving water may erode the road or the shoulder of the road, forming unseen traps for pedestrian and/or vehicular traffic. Consequently, flood-related accidental deaths frequently occur as the result of an attempt to move a stalled vehicle. 
         [0005]    Safety personnel and organizations have tried several approaches, not only to reducing risks to travelers&#39; lives and property from flooding, but also to keep translation flowing during floods. Weather alerts only notify in-route vehicles of floods based on information coming from weather radar or satellites. Hazard alerts notify in-route vehicles of accidents, flooding, and construction on local roads and facilitate finding alternative routes to avoid potentially problematic areas. Weather based route generation has been used to generate routes based on current and predicted weather for an area. Other alerts provide travel information on closed roads and areas, travel delays and other travel issues. 
         [0006]    Unfortunately, these approaches use relatively brute force routing techniques. These techniques primarily focus on generating a route and one or more alternatives based on fixed criteria. The results notify the traveler of potential hazards, including floods, along the way. These techniques do not, however, inform the travelers of the severity of risk of incidents along the particular route, e.g., whether there is a remote possibility of flooding, as opposed to a high likelihood of areas of rapidly moving floodwaters of frequent accidents occurring during previous flooding. 
         [0007]    Thus, there is a need for making the travelers aware of risks in selecting a route to a selected destination and more particularly in assessing increased risk of incidents caused by flooding that occurs along routes to a selected destination and providing notification of the associated risks of those incidents to facilitate route selection. 
       SUMMARY OF THE INVENTION 
       [0008]    A feature of the invention is associating flooding with routes provided to a selected location; 
         [0009]    Another feature of the invention is generating multiple routes to a designation with the risk of hazard associated with incidents occurring along each route; 
         [0010]    Yet another feature of the invention is that a traveler is able to designate a destination that lies on the other side of a flood zone or zones, receive a set of routes to the destination through the flood zone(s) with each route having an associated hazard risk indicating the likelihood of incidents along each of the routes. 
         [0011]    The present invention relates to a travel routing system, method and program product therefor. A location detector detects a current location. A geographical database provides details of a given area. Selecting a destination causes a route generator to generate routes through the area from the current location. A flood simulator receives meteorological data and determines flooding along the routes. A risk-modeling unit determines the risk to travelers of using each route. Before the risk-modeling unit is deployed, it is trained off-line to model travel risks using incidents in an incident data store and simulated flooding in the vicinity of the incidents. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0012]    The foregoing and other objects, aspects and advantages will be better understood from the following detailed description of a preferred embodiment of the invention with reference to the drawings, in which: 
           [0013]      FIGS. 1A  and B show an example of traffic routing during flooding situations using a flood-risk-modeling unit according to a preferred embodiment of the present invention; 
           [0014]      FIG. 2  shows an example of mapped real time meteorological iconically representing weather from flood simulation; 
           [0015]      FIG. 3A  shows a mapped example of a risk analysis model with risk iconically indicated and generated from the flood simulation map; 
           [0016]      FIG. 3B  shows an example of a risk table for risk of incidents along routes from the mapped example. 
       
    
    
     DESCRIPTION OF PREFERRED EMBODIMENTS 
       [0017]    As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon. 
         [0018]    Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. 
         [0019]    A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. 
         [0020]    Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. 
         [0021]    Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). 
         [0022]    Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
         [0023]    These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks. 
         [0024]    The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
         [0025]    Turning now to the drawings and more particularly,  FIGS. 1A  and B show an example of traffic routing during flooding situations using a flood-risk-modeling unit  100 , e.g., a flooding aware Global Positioning System (GPS), according to a preferred embodiment of the present invention. Preferably, each preferred flood-risk-modeling unit  100 , e.g., a stand-alone Bayesian network node or a stand-alone neural network node, is trained offline  110 ; and then, the trained flood-risk-modeling unit  100  is deployed  120  for real time route generation according to a preferred embodiment of the present invention. 
         [0026]    The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. 
         [0027]    Offline training  110  does not rely on real-time data, but instead uses meteorological history data  112 , geographical data  114 , incident data  116  and simulated weather patterns and results  118 , e.g., using a computational numerical simulator by the unit  100  itself, or remotely, on a mainframe computer (not shown) to train the preferred flood-risk-modeling unit  100 . Once trained, the preferred flood-risk-modeling unit  100  is deployed and may be carried by a user or hosted by a mobile platform, and generating routes for the user. So, the trained unit  100  is deployed  120 , e.g., in a flood-risk aware GPS unit, such as a dash board GPS, a smart phone, or a tablet computer. 
         [0028]    Preferably, two types of historical data meteorological history data  112  and incident data  116  are used in training the preferred flood-risk-modeling unit  100 . Meteorological data  112  includes weather information such as precipitation, ambient temperature and winds, preferably taken from weather history for the area in the geographical data  114 . Incident and accident data  116  lists incidents/accidents and indicates when (date and time), where (geographical coordination points), how (brief description plus any categorization available) each incident/accident happened, and the severity of each occurrence, again preferably taken from incident history for the area in the geographical data  114 . 
         [0029]    Geographical data  114  is essentially a virtual relief map of, for example, streets, roads, parks and a topological catalog of an area, e.g., rivers, streams, ditches, high points (e.g., hills and mountains) and low points (e.g., valleys) as well as respective altitudes. Moreover, preferably, the meteorological history data  112 , geographical data  114  and incident data  116  include real history, incidents and location(s), with a full range of history, incidents, location(s) sufficient for training the preferred flood-risk-modeling unit  100 . Thus, the geographical data  114  may be updated and/or supplemented based on subsequent field experience. 
         [0030]    A flooding simulator  118  provides a flood forecast using water depth for each point in the domain throughout a given time horizon. In particular, the flood forecast is a hydrological model of a location, e.g., city, state or country, that describes the behavior of surface rain water runoff. The flooding simulator  118  applies a typical well known numerical method to the hydrological location model to provide a solution that describes the area for the particular weather conditions described by data input to the model. Typical input data to the flooding simulator  118 , in this example, includes topography information  114  (e.g., geolocation and ground elevation), boundary and initial conditions  112  and precipitation forecast data, past (also  112 ) and present. 
         [0031]    The preferred flood-risk-modeling unit  100  trains to generate flood caused incident risk rated routes. Training uses the hydrological location model  118  with history data  112  and incident data  116  to build a risk model, e.g., using state of the art artificial intelligence (AI) techniques such as stand-alone neural networks and stand-alone Bayesian networks. The risk model correlates incidents/accidents with meteorological data and flood level for different locations and particular meteorological and flooding conditions. Once trained, the preferred flood-risk-modeling unit  100  may be deployed, e.g., sold as a standalone unit or installed with GPS on a motor vehicle, for routing travelers and providing the risk associated with those routes in real time. 
         [0032]    The deployed flood-risk-modeling unit  100  of  FIG. 1B  includes geographical data storage  122  and has access to a flood simulator  124  and real time meteorological information  126 . The geographical data storage  122  includes data describing the intended operating area, e.g., a single state or country, and may be the same simulator  118  used in training the unit  100 . The flood simulator  124 , which may be located remotely or, preferably, with or, part of, the deployed flood-risk-modeling unit  100 , may be the same simulator  118  used in training the unit  100 . The source of real time weather information  126 , e.g., weather sensors and/or data from the National Weather Service, for example, provides real-time meteorological data, instead of the meteorological history data  112  provided during training  110 . 
         [0033]    Once deployed  120 , the preferred flood-risk-modeling unit  100  routes travel  120  based on user input  128 , e.g., selecting a destination on a touch screen display  130 , and the current location  132 , e.g., of the mobile platform or vehicle detected by a GPS. The flood-risk-modeling unit  100 , e.g., the GPS, generates a set of available routes between the initial location and the destination. At this time the flood simulator  124  retrieves real time and predicted weather data  126  and geographical data  124  to generate a current hydrological model of the area encompassing the endpoints. 
         [0034]      FIG. 2  shows an example of mapped  140  real time meteorological iconically representing weather  142  from flood simulation  124 . The extent of flooding is indicated by cloud  142  clusters with the number of clouds in each cluster indicating how heavy flooding is in each particular location. 
         [0035]      FIG. 3A  shows a mapped  150  example of risk results from the risk analysis model prior to application to routes with each risk  152  iconically indicated and generated from the flood simulation map of  FIG. 2 . Driving hazards are indicated by clusters of crash icons  152  with the number in each indicating the severity of the local hazard. The flood-risk-modeling unit  100  generates multiple routes, preferably ranked according to the flood level, incident risk and length. 
         [0036]      FIG. 3B  shows an example of a risk table  154  indicating risk of incidents along routes and generated from mapped example  150 . In this example, routes are listed  154  in ascending order of driving distance. Preferably, the flood-risk-modeling unit  100  presents the routes and corresponding incident risk ranking, e.g., displayed on a local screen, from which a route may be selected based on incident risk. Optionally, a trip may be re-routed or updated periodically, while moving towards the destination, reassessing risks as weather conditions and flood estimates change. 
         [0037]    Thus advantageously, the preferred flood-risk-modeling unit generates a set of translation routes for people and mobile platforms to follow that reduce incident or accident risks and keep the translation flowing in floods. Water level and incident risks are considered in generating the routes from the source to the final destination. Accordingly, the preferred flood-risk-modeling unit simplifies translation and reduces flooding accident risks by providing detailed route information to users for making better informed choices. 
         [0038]    While the invention has been described in terms of preferred embodiments, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the appended claims. It is intended that all such variations and modifications fall within the scope of the appended claims. Examples and drawings are, accordingly, to be regarded as illustrative rather than restrictive.