Patent Publication Number: US-2020284601-A1

Title: Interactive telematics system

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to U.S. Provisional Patent Application No. 62/266,420, filed Dec. 11, 2015, the entire contents of which is hereby incorporated by reference. 
    
    
     BACKGROUND 
     Existing mapping systems allow a driver to select a fastest or shortest route or one that avoids tolls or highways. Existing mapping systems, however, do not identify an optimum route based a user&#39;s unique personality and preferences (or the unique attributes or limitations of the user&#39;s vehicle). Some individuals may prefer to travel on roadways with lower speed limits, such as a teenage female with a limited driving history, a user with a history of traffic tickets, a user with limited insurance coverage, a user who typically travels with an infant, etc. Other users may seek out roadways with multiple lanes that are in good condition to allow for travel at higher speeds, such as an older male driver, an experienced driver who often drives an expensive, all-wheel-drive car, etc. Meanwhile, the preferred routes of each user may change depending on the dynamically changing road conditions and/or weather conditions. Additionally, certain roadways may be closed to certain vehicle types (e.g., trucks) or vehicles over a certain weight or may include highway overpasses that are too low for vehicles over a certain height. 
     Accordingly, there is a need for a system that identifies the optimum routes for a user based on the user&#39;s unique preferences while accounting for the dynamically changing road conditions and the current and/or forecasted weather conditions. Additionally, there is a need for the system to identify those optimum routes based on the unique attributes or limitations of the user&#39;s vehicle. 
     SUMMARY 
     In order to overcome those and other drawbacks in the prior art, there is provided an interactive telematics system that identifies one or more optimum routes for a user by identifying a plurality of potential routes from a departure location to a destination, calculating attributes of each of the potential routes, comparing the attributes of each of the potential routes to user preferences in a user profile associated with the user, identifying one or more optimized routes for the user by selecting one or more of the potential routes based on the comparison of the attributes of each of the potential routes to the user preferences associated with the user, and outputting the one or more optimized routes to a communications network for transmittal to a remote device associated with the user. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Aspects of exemplary embodiments may be better understood with reference to the accompanying drawings. The components in the drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of exemplary embodiments, wherein: 
         FIG. 1  is a diagram illustrating an architecture of an interactive telematics system according to an exemplary embodiment of the present invention; 
         FIG. 2  is a block diagram illustrating the interactive telematics system according to an exemplary embodiment of the present invention; 
         FIG. 3  is a drawing illustrating three potential routes from a departure location to a destination location; 
         FIG. 4  is a drawing illustrating a fourth potential route from the departure location to the destination location; 
         FIG. 5  is a flowchart illustrating a process for determining one or more optimized routes for a user and outputting those routes to the user according to an exemplary embodiment of the present invention; 
         FIG. 6  is a flowchart illustrating a process for updating a user profile according to an exemplary embodiment of the present invention; and 
         FIG. 7  is a flowchart illustrating a process for updating correlations used to calculate the attributes of potential routes according to an exemplary embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     Reference to the drawings illustrating various views of exemplary embodiments of the present invention is now made. In the drawings and the description of the drawings herein, certain terminology is used for convenience only and is not to be taken as limiting the embodiments of the present invention. Furthermore, in the drawings and the description below, like numerals indicate like elements throughout. 
       FIG. 1  is a diagram illustrating an architecture  100  of an interactive telematics system according to an exemplary embodiment of the present invention. 
     As shown in  FIG. 1 , the architecture  100  includes remote devices  120  that communicate with one or more servers  140  and one or more storage devices  150  via one or more networks  130 . As described in detail below, the system is configured to output telematics information to the remote devices  120 . 
     The remote devices  120  include any suitable computing device configured to receive information from the one or more servers  140  via the one or more networks  130 . Remote devices may include, for example, smartphones, desktop computers, notebook computers, in-vehicle navigation devices, stand-alone navigation devices, etc. Each remote device  120  may include one or more processors (e.g., a central processing unit, a graphics processing unit, etc.), one or more storage devices (e.g., random access memory, read-only memory, solid state memory, a hard disk, etc.) as well as at least one input device (e.g., a keyboard, a mouse, etc.) and output device (e.g., a display) or an input-output device (e.g., a touchscreen). The remote devices  120  and/or the network(s)  130  may determine the real-time locations of at least some of the remote devices  120 , for example using the Global Positioning System (GPS), network identification, cellular network triangulation, etc. 
     The one or more servers  140  may include any suitable computing device that executes instructions to perform the functions described herein. The one or more servers  140  may include internal storage and one or more computer processors. The one or more storage devices  150  may also include a non-transitory computer readable storage medium, such as a hard disk, solid-state memory, etc. The network(s)  130  may include one or more short- or long-range data connections that enable the one or more servers  140  to output information for transmittal to (and receive information from) the remove devices  120 . The data connections may include wired and/or wireless data connections. The network(s)  130  may include one or more local area networks or wide area networks (e.g., cellular networks, the internet). 
     In order to perform the functions described herein, the one or more servers  140  may receive information from third party sources. 
     The one or more servers  140  may receive past and current traffic data  170 . Past traffic data  170  may be received, for example, from (federal, state, and/or local) government entities, automobile associations (e.g., the American Automobile Associations), etc. Current traffic data  170  may be received, for example, from government entities, private traffic management organizations, etc. 
     The one or more servers  140  may receive static and/or dynamic road condition data  180 . Road condition data may be received, for example, from government agencies (e.g., federal, state, and local departments of transportation, topographical information from the U.S. Geological Survey, etc.), private traffic management organizations, etc. 
     The one or more servers  140  may receive current, historical, and forecasted weather data  190 . The weather data  190  may be received from third parties such as AccuWeather Enterprise Solutions, Inc., governmental agencies (e.g., the U.S. Environmental Protection Agency (EPA), the National Weather Service (NWS), the National Hurricane Center (NHC), Environment Canada, the U.K. Meteorologic Service, the Japan Meteorological Agency, etc.), other private companies (e.g., Vaisalia&#39;s U.S. National Lightning Detection Network, Weather Decision Technologies, Inc.), individuals (e.g., members of the Spotter Network), etc. 
       FIG. 2  is a block diagram illustrating the interactive telematics system  200  according to an exemplary embodiment of the present invention. 
     As shown in  FIG. 2 , the interactive telematics system  200  includes an analysis unit  230  and a geographic information system (GIS)  232 , a user profile database  240 , a roadway database  250 , and a device location database  260 . The interactive telematics system  200  may also include a traffic database  270 , a road condition database  280 , and a weather condition database  290 . The user profile database  240  includes user profiles  242  and may also include vehicle profiles  244 . The traffic condition database  270  includes past traffic conditions  272  and current traffic conditions  274 . The traffic condition database  270  may also include predicted traffic conditions  276  determined by the interactive telematics system  200 . The road condition database  280  includes static road conditions  282  and may also include dynamic road conditions  284 . The weather condition database  290  includes past weather conditions  292 , current weather conditions  294 , and forecasted weather conditions  296 . 
     The analysis unit  230  may include any suitable computing device and/or computer executable software instructions that perform the functions described herein. The analysis unit  230  may be realized by hardware elements, such as the one or more servers  140 , and/or software instructions accessible to and executed by the one or more servers  140 . 
     The geographic information system (GIS)  232  may be any suitable computing device and/or computer executable software instructions designed to capture, store, manipulate, analyze, manage, and/or present geographical data. (Geographic information systems are sometimes referred to as geographical information systems.) The GIS  232  may be realized by special-purpose hardware and/or software instructions executed by the one or more servers  140 . Additionally or alternatively, the interactive telematics system  200  may use a third party GIS, such as Google maps, Ersi, etc. 
     The user profile database  240 , the roadway database  250 , the device location database  260 , the traffic condition database  270 , the road condition database  280 , and the weather condition database  290  may be any organized collection of information, whether stored on a single tangible device or multiple tangible devices. The user profile database  240 , the roadway database  250 , the device location database  260 , the traffic condition database  270 , the road condition database  280 , and the weather condition database  290  may be stored, for example, in one or more of the storage devices  150 . 
     The user profile database  240  stores a plurality of user profiles  242 , each user profile  242  including information used by the interactive telematics system  200  to determine the user&#39;s preferred driving behavior and/or preferred routes. Each user profile  242  may include, for example, demographic information such as age and sex, known medical conditions, level of driving experience, behavior type, risk adversity, tendencies and preferences with such things as cruising speed, responses to various traffic conditions, and reactions to adverse and potentially dangerous driving conditions, the usual co-occupants with the driver (e.g., if the user drives alone, with small children, elderly people, people with known medical conditions, etc.), driving record, current type of insurance coverage, and other factors determined by the interactive telematics system  200  as relevant to the user&#39;s preferred driving behavior and preferred routes. Each user profile  242  may include information received directly from the user and/or information determined by the interactive telematics system  200  (e.g., based on the user&#39;s driving behavior as inferred by the real-time location of the user&#39;s remote device  120 ). 
     The user profile database  240  may also store a plurality of vehicle profiles  244  associated with vehicles used by users of the interactive telematics system  200 . Each vehicle profile  244  may include information used by the interactive telematics system  200  to determine the user&#39;s preferred driving behavior and/or preferred routes when driving the vehicle associated with the vehicle profile  244 . Each vehicle profile  244  may include attributes of the vehicle associated with the vehicle profile  244 , such as vehicle height, vehicle type (e.g., sedan, convertible, truck, etc.), vehicle fuel requirements (e.g., diesel and diesel grade, gasoline and gasoline grade, liquefied natural gas, etc.), vehicle age, vehicle weight, vehicle transmission type (automatic, manual), vehicle drivetrain (e.g., two-wheel drive, four-wheel drive, all-wheel drive, etc.), vehicle service/maintenance history, required vehicle maintenance (e.g., information relating to the vehicle&#39;s known problems), etc. The vehicle profiles  244  may be determined based on information from users. For example, a user may contribute information for use in vehicle profile  244  by answering questions posed by the interactive telematics system  200  via a mobile phone application, an online form, etc. A user may input information regarding one or more vehicles that are used by another user (or multiple users) in the same household. 
     The roadway database  250  includes a dataset of current roadways, including available opportunities for adjusting traffic flow (e.g., parallel access roads, passing lanes, on- and off-ramps, etc.). The dataset of current roadways may be received from government agencies, private traffic management organizations, etc. 
     The device location database  260  includes information indicative of the real-time locations of at least some of the remote devices  120 . Real-time locations of remote devices  120  may be determined by the remote devices and/or the network(s)  130 , for example using the Global Positioning System (GPS), network identification, cellular network triangulation, etc. Additionally, the device location database  260  may be automatically and/or repeatedly updated to include information indicative of the real-time (or near real-time) dynamic location of at least some of the remote devices  120 . 
     The traffic condition database  270  includes information regarding past traffic conditions  272  and current traffic conditions  274 . The traffic conditions  272  and  274  may include, for example, the speed and volume of traffic at points and/or segments of the roadways included in the roadway database  250 , the composition of that traffic (e.g., long haul tractor trailers, passenger vehicles, pick-up trucks pulling trailers, motorcycles, etc.), collision locations, the nature and severity of those collisions, etc. Each data point regarding the traffic conditions  272  and  274  is stored with the date and time of that data point. The past and current traffic conditions  272  and  274  may be determined based on information from third party sources (e.g., the traffic data  170  described above) and/or determined by the interactive telematics system  200  based on the real-time locations of the remote devices  120  (e.g., the speed of the remote device  120 , whether the remote device  120  is stopping frequently, etc.). As described in detail below, the interactive telematics system  200  may also use the past traffic conditions  272  and the current traffic conditions  274  (as well as additional information) to determine and store predicted traffic conditions  276 , including estimated likelihoods of collisions, and store the predicted traffic conditions  276  in the traffic condition database  270 . 
     The road condition database  280  includes static road conditions  282  for segments of the roadways included in the roadway database  250 . The static road conditions  282  may include, for example, the applicable traffic laws (e.g., speed limit, permitted vehicle types, etc.), roadway types (e.g., a multi-lane interstate highway, a two-lane roadway, one-lane county roadway, etc.), overpass heights, location (e.g., desert, mountains, suburban, urban, etc.), surface composition (e.g., asphalt, concrete, gravel composite, etc.), the amount of illumination at night, etc. The static road conditions  282  may be determined by the interactive telematics system  200  based on information received from third party sources (e.g., the road condition data  180  described above) and/or feedback from users. 
     The road condition database  280  may also include dynamic road conditions  284  for segments of the roadways included in the roadway database  250 . The dynamic road conditions  284  may include, for example, surface conditions (e.g., wet, snow-covered, icy, dry, etc.), surface temperature, surface maintenance conditions (e.g., properly maintained or in poor repair), construction activity (e.g., locations and nature of construction activities), time periods during which roadways or segments of roadways are closed (e.g., for recreation), etc. The interactive telematics system  200  may determine the dynamic road conditions  284  based on information received from sensors (e.g., weather and/or environmental sensors), information received from third party sources (e.g., the road condition data  180  and/or the weather data  190  described above), feedback from users, etc. Data points regarding dynamic road conditions  284  may be stored with the date of that data point. Additionally, data points regarding dynamic road conditions  284  may be stored with the time of that data point (for example, if a dynamic road condition  284  is not applicable for an entire day). 
     The weather condition database  290  includes any information regarding any atmospheric, environmental, geographic, and/or geological condition that may have affected past traffic conditions  272 , may be affecting current traffic conditions  274 , or may affect future traffic conditions, including past weather conditions  292 , current weather conditions  294 , and forecasted weather conditions  296 . Weather conditions may include weather parameters such as temperature, precipitation, visibility, wind speed and direction, etc. The forecasted weather conditions  296  may be determined by the interactive telematics system  200  or received from a weather forecasting system or third party. The forecasted weather conditions  296  may be location-specific, minute-by-minute forecasts generated using AccuWeather&#39;s MinuteCast system. (MINUTECAST is a registered service mark of AccuWeather, Inc.) Additionally, the weather condition database  290  may include geographical conditions (e.g., the potential for glare along projected routes), environmental conditions (e.g., the known habitats or projected travel paths of animals such as birds), geological conditions (e.g., past locations and potential future locations of earthquakes), etc. 
     The current traffic conditions  274 , the dynamic road conditions  284 , and/or the current weather conditions  294  may also be determined based on information received from remote devices  120 , vehicles, and/or individuals. In one example, the interactive telematics system  200  may receive and interpret point observations from individuals, such as images and/or descriptions, and incorporate information from those point observations (as well as the location of the user) when determining the current traffic conditions  274 , the dynamic road conditions  284 , and/or the current weather conditions  294 . The point observations may be output by users for transmittal to the interactive telematics system  200  (for example, using a graphical user interface of a remote device  120 ). Additionally or alternatively, the interactive telematics system  200  may gather point observations from social media, other publicly-available sources, and/or private third-party sources. In another example, the interactive telematics system  200  may receive and interpret information from vehicles and incorporate that information (as well as the location of the vehicle) when determining the current traffic conditions  274 , the dynamic road conditions  284 , and/or the current weather conditions  294 . The information from vehicles may include sensor data from vehicle weather sensors (e.g., outside temperature and rain sensors), sensor data from vehicle weather road condition sensors (e.g., sensors used by a vehicle anti-lock braking system to determine wet or snow-covered roads or vehicle traction), sensor data from other vehicle sensors (e.g., cameras), information indicating that the vehicle lights are on during the day (indicating reduced visibility), information that vehicle windshield wipers are on (indicating rain), etc. The information from vehicles may be output to the interactive telematics system  200  via an in-vehicle remote device  120 , a remote device  120  that is paired with the vehicle (e.g., via Bluetooth), etc. 
     The interactive telematics system  200  determines optimized driving routes for a user based on characteristics of that user stored in a user profile for that user. The system will be described with reference to the three routes illustrated in  FIG. 3 . 
       FIG. 3  illustrates three potential routes from a departure location  310  to a destination location  390 , including route  301 , route  302 , and route  303 . Each of the routes  301 ,  302 , and  303  are determined by the analysis unit  230  based on information stored in the roadway database  250  using the GIS  232 . 
     As shown in  FIG. 3 , route  301  is 24.9 miles in length with an estimated travel time (determined by the analysis unit  230  as described below) of 1 hour, 9 minutes. Route  302  is 22.1 miles in length with an estimated travel time of 1 hour, 2 minutes. Route  303  is 22.3 miles in length with an estimated travel time of 1 hour. In addition to length l and estimated travel time t, the interactive telematics system  200  determines other attributes of each potential route, including, for example, the potential safety risk of traveling on each route (or, inversely, the safety s) and other factors of the driving experience along each route, such as potential congestion c, whether the route is scenic (scenery p), whether the route is well lit at night (brightness b), etc. For example, the analysis unit  230  may reduce each of those attributes to a numerical value are shown in Table 1: 
     
       
         
           
               
               
               
               
               
               
             
               
                   
                 TABLE 1 
               
               
                   
                   
               
             
            
               
                   
                 Route 
                 301 
                 302 
                 303 
                 n 
               
               
                   
                 Length 
                 l 301   
                 l 301   
                 l 301   
                 l n   
               
               
                   
                 Travel time 
                 t 301   
                 t 301   
                 t 301   
                 t n   
               
               
                   
                 Safety 
                 s 301   
                 s 301   
                 s 301   
                 s n   
               
               
                   
                 Brightness 
                 b 301   
                 b 301   
                 b 301   
                 b n   
               
               
                   
                 Congestion 
                 c 301   
                 c 301   
                 c 301   
                 c n   
               
               
                   
                 Scenery 
                 p 301   
                 p 301   
                 p 301   
                 p n   
               
               
                   
                 . . . 
                 . . .  
                 . . .  
                 . . .  
                 . . .  
               
               
                   
                 . . . 
                 . . .  
                 . . .  
                 . . .  
                 . . . 
               
               
                   
                   
               
            
           
         
       
     
     Whether a particular route n is appealing to a particular user can then be expressed mathematically as X n , as shown in Equation 1: 
         X   n   =Al   n   +Bt   n   +Cs   n   +Db   n   +Ec   n   +Fp   n  . . . 
     where A, B, C, D, E, F, etc. are coefficients representing the user preferences for each attribute relative to the other attributes. In other words, the ratio B:A represents how much the user weighs estimated travel time t n  versus distance l n  when determining an optimum driving route. Similarly, the ratio B:C represents how much the user weighs estimated travel time t n  versus safety s n  (i.e., the user&#39;s risk aversion), the ratio B:D represents how much the user weighs estimated travel time t n  versus traveling on roads that are well lit (with a high b n ), the ratio B:E represents how much the user weighs estimated travel time t n  versus congestion c n  (e.g., how much the user would prefer a longer drive where he or she keeps moving to a shorter one in traffic), the ratio B:F how much the user weighs estimated travel time t n  versus scenery p n  (e.g., whether and by how much the user would prefer a longer drive with a nice view), etc. 
     The analysis unit  230  determines each attribute l n , c n , etc. for each potential route. Because some of the attributes may vary over time, the interactive telematics system  200  may provide functionality for the user to specify a departure time (or alternatively an estimated arrival time) via a graphical user interface using a remote device  120 . Of course, the interactive telematics system  200  may use the current time as the default departure time. 
     To determine the distance l n  of each route, the analysis unit  230  simply plots the route from the departure location  310  to the destination location  390  and measures the linear length of the route using the GIS  232 . 
     If the departure time is the current time, the analysis unit  230  determines potential congestion c n  largely based on the current traffic conditions  274 . However, because congestion may vary during the time it takes for the user to travel along the route, the analysis unit  230  may additionally determine potential congestion c n  based on past traffic conditions  272  along the route at similar times of day, during similar days of the week, on similar days of the year (e.g., holiday or non-holiday), when the past weather conditions  292  were similar to the current weather conditions  294  and/or forecasted weather conditions  294  (depending on when the user is expected to be traveling along that portion of the route), when the dynamic road conditions  284  were similar to the current dynamic road conditions  284 , etc. Additionally, the analysis unit  230  may determine potential congestion c n  based on the past traffic conditions  272  of other similar roadways (i.e., roadways with similar static road conditions  282 ) at similar times of day, during similar days of the week, on similar days of the year (e.g., holiday or non-holiday), when the past weather conditions  292  were similar to the current weather conditions  294  and/or forecasted weather conditions  294  (depending on when the user is expected to be traveling along that portion of the route), when the dynamic road conditions  284  were similar to the current dynamic road conditions  284 , etc. 
     The analysis unit  230  determines the estimated travel time t n  based on the length of the route and an estimated driving speed of the vehicle, which is the inversely proportional to the potential congestion c n  determined by the analysis unit  230  as described above. 
     Similar to the potential congestion c n  determination, the analysis unit  230  also determines the safety s n  of each route based on past traffic conditions  272 . In this instance, however, the analysis unit  230  determines the safety s n  of the route based on past collisions along the route (a subset of the past traffic conditions  272 ). Past collisions may be given more weight if they were, for example, during similar times of day, during similar days of the week, on similar days of the year (e.g., holiday or non-holiday), when the past weather conditions  292  were similar to the current weather conditions  294  and/or forecasted weather conditions  294  (depending on when the user is expected to be traveling along that portion of the route), when the dynamic road conditions  284  were similar to the current dynamic road conditions  284 , etc. Additionally, the analysis unit  230  may further determine the safety s n  of the route based on past collisions along similar roadways (i.e., roadways with similar static road conditions  282 ) at similar times of day, during similar days of the week, on similar days of the year (e.g., holiday or non-holiday), when the past weather conditions  292  were similar to the current weather conditions  294  and/or forecasted weather conditions  294  (depending on when the user is expected to be traveling along that portion of the route), when the dynamic road conditions  284  were similar to the current dynamic road conditions  284 , etc. 
     Each time the analysis unit  230  determines the potential congestion c n , the estimated travel time t n , and the safety s n  of each route, the analysis unit  230  may store those calculations as predicted traffic conditions  276 . After the time period for those calculations, the analysis unit  230  may compare those predicted traffic conditions  276  to the actual traffic conditions (i.e., the current traffic conditions  274  or the past traffic conditions  272 , depending on when the comparison takes place) and the actual travel times for users along that route. Depending on the accuracy of the calculations, the analysis unit  230  can further refine the correlations used to make those calculations. 
     The analysis unit  230  may determine how scenic (i.e., scenery p n ) and/or how well lit (i.e., brightness b n ) the route is based on the static road conditions  282  for each portion of the route. Because scenery p n  may only be relevant during the day and brightness b n  is only relevant at night, the analysis unit  230  may vary those factors based on time of day. Alternatively, the analysis unit  230  may vary user preferences regarding those attributes (e.g., the coefficients D and E) based on time of day. 
     The user preferences used by the analysis unit  230  to determine the user&#39;s preferred driving behavior and/or preferred routes (for example, information used to determine the coefficients A, B, C, D, E, F, etc. and/or the ratios B:A, B:C, B:D, B:E, B:F, etc., as described above) are stored in a user profile  242  associated with the user. The analysis unit  230  may determine those user preferences, for example, based on information received directly from the user (e.g., by providing functionality for the user to input information via a graphical user interface provided by the via a graphical user interface using a remote device  120 ). For example, the graphical user interface may ask the user direct questions about the user&#39;s preference for scenery p n  and/or safety s n  relative to trip length l n , whether the user prefers well lit roads (i.e., low brightness b n ) at night, whether the user prefers well lit roads at night when it is raining, etc. 
     Additionally, the user profile  242  may store information that is directly applicable to certain routes. Referring back to  FIG. 3 , for example, a parent may not permit a new driver to travel along a portion of route  301 . Accordingly, the interactive telematics system  200  may provide functionality for the user (e.g., the new driver) or another user (e.g., the parent) to specify that certain roadways or portions of roadways are to be avoided. Accordingly, the analysis unit  230  will output only routes that avoid those roadways. 
     Additionally, in the course of providing optimized routes for the user, the analysis unit  230  may present the user with more multiple route options (for example, as shown in  FIG. 3 ), allow the user to select one of the routes, and infer from the user selection that the user prefers the attributes of the selected route relative to the attributes of the routes that the user chose not to select. Additionally, because the analysis unit  230  has access to information indicative of the real-time location of the remote device  120  associated with the user (as stored in the device location database  260 ), the analysis unit  230  may infer that the user prefers the attributes of the routes that the user chooses to follow, even if the user chooses to drive along a route without requesting an optimized route from the interactive telematics system  200 , chooses to deviate from a route suggested by the interactive telematics system  200 , etc. 
     Additionally, the analysis unit  230  may infer that the user has similar user preferences as other users with similar user profile criteria as the user profile criteria stored in the user profile  242  associated with the user, such as age, sex, medical condition(s), driving experience, driving record, insurance, usual co-occupant(s) (e.g., children, elderly people, people with medical conditions, etc.), and/or similar vehicle profile criteria as the vehicle profile criteria stored in the vehicle profile  242  associated with the user&#39;s vehicle, such as vehicle type (e.g., sedan, convertible, truck, etc.), vehicle fuel requirements (e.g., diesel and diesel grade, gasoline and gasoline grade, liquefied natural gas, etc.), vehicle age, vehicle weight, vehicle transmission type (automatic, manual), vehicle drivetrain (e.g., two-wheel drive, four-wheel drive, all-wheel drive, etc.), vehicle service/maintenance history, and/or required vehicle maintenance (e.g., information relating to the vehicle&#39;s known problems). 
     The user&#39;s preferred driving behavior and/or preferred routes may vary for different types of trips. For example, the user may prefer routes with more scenery p n  for trips of longer lengths (i.e., higher l n ). In another example, a user safer routes (i.e., higher safety s n ), routes with fewer highways, and/or routes with lower speed limits when the user is driving a specific vehicle, etc. Accordingly, the analysis unit  230  may determine specific user preferences for certain types of trips—for example, by asking the user specific questions about user preferences for certain types of trips, inferring those specific preferences based on user-selected routes and/or user-driven routes for certain types of trips, etc.—and determine optimized routes for those types of trips based on those specific preferences. 
     The user&#39;s preferred driving behavior and/or preferred routes may vary based on adverse weather conditions. For example, a user may prefer safer routes (i.e., higher safety s n ), routes with fewer highways, and/or routes with lower speed limits when the current weather conditions  294  and/or forecasted weather conditions  296  show that the user will be driving in adverse weather conditions. A user&#39;s specific preferences may even vary based on a specific weather condition. For example, a user may prefer routes with higher brightness b n  when the current weather conditions  294  and/or forecasted weather conditions  296  show that the user will be driving in the rain. Accordingly, the analysis unit  230  may determine specific user preferences for trips during adverse weather conditions—for example, by asking the user specific questions about user preferences for during adverse weather conditions, inferring those specific preferences based on user-selected routes and/or user-driven routes during adverse weather conditions, etc.—and determine optimized routes for trips during adverse weather conditions. 
     The analysis unit  230  may also learn new routes that the user prefers based on the real-time locations of the remote device  120  associated with the user. As shown, for example, in  FIG. 4 , the user may select route  301  when leaving the departure location  310  then later decide to deviate from route  301  and instead follow route  404  (despite the fact that the interactive telematics system  200  did not present route  404 ). Later, if the user is making a similar trip and route  301  is presented as an option, the analysis unit  230  may also present route  404  as an option along with, for example, the estimated travel times t 301  and t 404 , so that the user may make a more informed decision of whether to follow route  301  or, once again, choose route  404 . 
     The analysis unit  230  may also determine optimized routes directly from vehicle profile criteria stored in the vehicle profile  242  associated with the user&#39;s vehicle. As shown in  FIGS. 3 and 4 , for example, a portion of route  302  may be closed to certain vehicle types (e.g., trucks) and/or vehicles over a certain weight. In another example, the route  301  may include a highway overpass that is too low for vehicles over a certain height. Accordingly, the analysis unit  230  may be configured to suggest alternate routes and avoid roadways that are inaccessible to vehicles with certain vehicle profile criteria. 
       FIG. 5  is a flowchart illustrating a process  500  for determining one or more optimized routes for a user and outputting those routes to the user according to an exemplary embodiment of the present invention. 
     The user (and the associated user profile  242 ) is identified in step  502 . If the remote device  120  is a personal device, such as a smartphone, the analysis unit  230  identifies the user based on the user associated with the smart device  120 . For example, the user profile  242  associated with the user may include a device identifier code associated with the remote device  120 . In some instances, however, the remote device  120  may be used by multiple users (e.g., an in-car or stand-alone navigation system). In those instances, the interactive telematics system  200  may provide functionality for the user to identify the user using a graphical user interface of the remote device  120 . 
     In some embodiments, the vehicle (and an associated vehicle profile  244 ) may be identified in step  504 . For example, if the remote device  120  is an in-car navigation system, the remote device  120  may be associated with a vehicle profile  244  associated with the vehicle. In other instances, the interactive telematics system  200  may provide functionality for the user to identify the vehicle by selecting one of the user&#39;s vehicles using a graphical user interface of the remote device  120 . 
     A destination is received from the user in step  506 , for example, by providing functionality for the user to select a destination using a graphical user interface of the remote device  120 . 
     A departure location is determined in step  508 . If the user is using a location-aware remote device  120 , the interactive telematics system  200  may use the current location of the remote device  120  as the default departure location. Additionally, however, the interactive telematics system  200  may provide functionality for the user to identify a different departure location using a graphical user interface of the remote device  120 . 
     A departure time is determined in step  510 . The interactive telematics system  200  may use the current time as the default departure time. Additionally, however, the interactive telematics system  200  may provide functionality for the user to identify a different departure time or a destination time using the remote device  120  (for example, by making a selection via a graphical user interface). 
     Potential routes from the departure location to the destination location are determined in step  512 . The interactive telematics system  200  may determine any number of potential routes using the GIS  232  and information stored in the roadway database  250 . 
     One or more of the potential routes may be eliminated based on information stored in the user profile  242  in step  514 . As described above, for example, the user profile  242  may indicate that the user prefers not to (or is not allowed to) travel along certain roadways or portions of roadways. Accordingly, the interactive telematics system  200  may eliminate the routes that include the roadways or portions of roadways that the user prefers to or must avoid. 
     One or more of the potential routes may be eliminated based on information stored in the vehicle profile  244  in step  516 . As described above, for example, the vehicle profile  244  may indicate that the vehicle is prohibited from traveling along certain roadways or portions of roadways. Accordingly, the interactive telematics system  200  may eliminate the routes that include those roadways or portions of roadways. 
     Attributes of each route (e.g., length l, estimated travel time t, safety s, potential congestion c, scenery p, brightness b, etc.) are calculated in step  518  as described above. 
     Some of the attributes of each route (e.g., congestion c, safety s, estimated travel time t, etc.) may be stored as predicted traffic conditions  276  in step  520 . 
     The interactive telematics system  200  determines one or more optimized routes in step  522 . The one or more optimized routes are determined by comparing the attributes of each potential route calculated in step  518  with user preferences stored in the user profile  242  associated with the user. Additionally or alternatively, the optimized route(s) may be determined further based on the vehicle profile  244  associated with the vehicle. 
     The one or more optimized routes are output to the user in step  524 . For example, the analysis unit  230  may output the one or more optimized routes to a network  130  for transmittal to the remote device  120  associated with the user and identified in the user profile  242 . 
     The process  500  may be performed by the analysis unit  230 . In some embodiments, the analysis unit  230  may include separate hardware devices and/or software module, each configured to perform some of the functions in the process  400 . For example, the analysis unit  230  may include a GIS  232  that determines potential routes in step  512 , a traffic analysis unit that calculates attributes of each potential route in step  518 , and an optimized route analysis unit that determines one or more optimized routes in step  524 . In other embodiments, the analysis unit  230  may include a single hardware device and/or software module may perform more than one of the functions described above. 
       FIG. 6  is a flowchart illustrating a process  600  for updating a user profile  242  according to an exemplary embodiment of the present invention. 
     If more than one route is output to the user in step  524 , a user selection of one of the routes may be received in step  602 . 
     The actual travel path of the user  604  may be determined based on the real-time locations of the remote device  120  associated with the user in step  604 . 
     In step  606 , the user profile  606  is updated based on the attributes of the route selected by the user in step  602  and/or the actual route traveled by the user as determined in step  604 . 
       FIG. 7  is a flowchart illustrating a process  700  for updating correlations used to calculate route attributes according to an exemplary embodiment of the present invention. 
     As described above, some of the attributes of each potential route that are calculated in step  518  (e.g., congestion c, safety s, estimated travel time t, etc.) may be stored as predicted traffic conditions  276  in step  520 . The actual attributes of those routes (e.g., congestion c, safety s, estimated travel time t, etc.) during those times are determined in step  702 . 
     In step  704 , the actual attributes of those routes are compared to the attributes calculated in step  518  and stored in step  520 . 
     In step  706 , the correlations used to calculate the route attributes in step  518  are updated based on the actual attributes of those routes as determined in step  702 . 
     While preferred embodiments have been set forth above, those skilled in the art who have reviewed the present disclosure will readily appreciate that other embodiments can be realized within the scope of the invention. Disclosures of specific numbers of hardware components, software modules and the like are illustrative rather than limiting. For example, five databases (a user profile database  240 , a roadway database  250 , a device location database  260 , a traffic condition database  270 , a road condition database  280 , and a weather condition database  290 ) are described in detail above with a description of information that may be included in each of those databases. As one of ordinary skill in the art would recognize, the information described above may be stored in any manner, so long as the information is accessible to the one or more one or more servers  140 . In other words, information described above as being included in one database may be stored in a different database, all of the information described above may be stored in a single database, etc. Accordingly, the present invention should be construed as limited only by the appended claims.