RU153473U1 - VEHICLE PLANNING WITH FUEL FUEL - Google Patents

Abstract

1. A device for planning a route of a vehicle taking into account fuel, comprising a computer on a vehicle, the computer comprising a processor and memory, the computer being configured to: determine an estimated fuel consumption for the route for the vehicle; determine at least partially based on the estimated fuel consumption that the amount of fuel in the vehicle is not enough for the vehicle to travel the route; recommend one or more intermediate route points within a predetermined route distance for refueling a vehicle. 2. The device of claim 1, wherein the computer is further configured to estimate fuel costs for the route at least partially based on estimated fuel consumption. The device according to claim 1, in which the estimated fuel consumption is based in part on comparing the collected data stored in the computer with the characteristics of the driver stored in the personalized hardware system. The device according to claim 1, in which the estimated fuel consumption is based in part on collected data stored on a computer related to at least one of: weather conditions, traffic conditions and construction conditions. The device according to claim 1, wherein the computer is further configured to recommend an intermediate waypoint based on at least one of a vehicle driving history and user input regarding a preferred intermediate waypoint. The device according to claim 1, in which the computer is additionally

Description

FIELD OF TECHNOLOGY

This application as a whole relates to systems (devices) for planning the route of a vehicle taking into account fuel.

BACKGROUND

Given a given starting point and a given destination or destination, the vehicle’s navigation system can formulate a suggested route for the vehicle. For example, a vehicle’s navigation system or other route-forming system can form a route to optimize travel time, minimize distance traveled, etc. However, the vehicle’s navigation systems have not been able to take into account certain available data regarding the history and current state of the vehicle, and have not been made to take into account some factors that may be relevant for planning the route of the vehicle. For example, there are no modern mechanisms for determining the state of fuel of a vehicle and for correcting a route, choosing an intermediate waypoint, etc.

For example, the application US 2013204520 A1, 08.08.2013, entitled "VEHICLE NAVIGATION SYSTEM" ("Vehicle Navigation System"), discloses a system that forms the route of the vehicle taking into account the allocated lane for a vehicle with a large number of passengers. CN 103344248 A, 09/10/2013, “Optimal path calculation method for vehicle navigation system”, discloses the calculation of the optimal path for a navigation system based on pivot points on a map with a grid, in wherein the intermediate node from one pivot point to an adjacent pivot point can be ignored, thereby significantly reducing the number of nodes that need to be processed. CN 103308055 A, 09/18/2013, “Vehicle road matching method of navigation system”, discloses an approach for comparing a road and a vehicle in which vehicle position information is used to coordinate with a confidence factor the roads.

However, none of the documents discloses systems (devices) for planning the route of a vehicle taking into account fuel.

US Pat. No. 8,185,302 B2, May 22, 2012, CONSERVATIONAL VEHICLE ROUTING, discloses a route definition with optimal fuel utilization based on estimated fuel consumption. The disclosed solution allows planning the route of the vehicle taking into account fuel, however, the objective of this solution is to determine the route with the optimal use of fuel based on the estimated fuel consumption. This solution is different from the solution disclosed in US 8185302 B2, and is intended to determine that the amount of fuel in the vehicle is not enough for the vehicle to travel the route, and to recommend one or more intermediate waypoints within a predetermined distance of the route for refueling the vehicle.

ESSENCE OF A USEFUL MODEL

In this application, disclosed options for a system (device) for planning the route of a vehicle taking into account fuel.

In particular, a system comprising a computer on a vehicle is disclosed, the computer comprising a processor and memory, the computer being configured to: determine an estimated fuel consumption for a route for a vehicle; determine, at least in part, based on the estimated fuel consumption, that the amount of fuel in

the vehicle is not enough for the vehicle to travel the route; and recommending one or more intermediate route points within a predetermined route distance for refueling a vehicle.

In a further aspect, the computer is further configured to estimate fuel costs for a route at least partially based on estimated fuel consumption.

In another further aspect, the estimated fuel consumption is based in part on comparing the collected data stored in the computer with the driver characteristics stored in the personalized hardware system.

In yet a further aspect, the estimated fuel consumption is based in part on collected computer data relating to at least one of weather, traffic, and construction conditions.

In yet a further aspect, the computer is further

configured to recommend an intermediate waypoint based on at least one of a vehicle driving history and user input regarding a preferred intermediate waypoint.

In yet a further aspect, the computer is further configured to use data received from a remote server to partially determine at least one of the estimated fuel consumption and one or more intermediate route points.

In yet a further aspect, the computer is further configured to use data received by driver input into the computer, in part to recommend one or more intermediate points on the route.

In yet a further aspect, the computer is further configured to: form at least a second route between the starting point and the final point and present each of the route and the second route for selection on a human-machine interface along with estimated fuel costs for each of the route and the second route.

In addition, a system comprising a computer on a vehicle is disclosed, the computer comprising a processor and memory, wherein the computer is configured to: identify the starting point and end point of the vehicle’s trip; form at least a first route and a second route between the starting point and the final point; determine, for each of the first route and the second route, the estimated fuel consumption for the vehicle; and issue each of the first route and the second route for selection on the human-machine interface, which also displays the estimated fuel costs for each of the first route and the second route.

In a further aspect, the estimated fuel consumption for at least one of the first route and the second route is based in part on comparing the collected data stored in the computer with the driver characteristics stored in the personalized hardware system.

In another further aspect, the estimated fuel consumption for at least one of the first route and the second route is based in part on collected computer data relating to at least one of weather, traffic, and construction conditions.

In yet a further aspect, the computer is further configured to recommend an intermediate waypoint for at least one of a first route and a second route based on at least one of a vehicle driving history and user input regarding a preferred intermediate waypoint.

In yet a further aspect, the computer is further configured to use data received from a remote server, in part to determine at least one of the estimated fuel consumption, first route, and second route.

A system comprising a computer on a vehicle is also disclosed, the computer comprising a processor and memory, wherein the computer is configured to: identify the starting point and end point of the vehicle’s trip; form a route between the starting point and the final point; generate the first estimated fuel consumption for the route; make the first decision, at least in part based on the estimated fuel consumption, that the amount of fuel in the vehicle is sufficient for the vehicle to travel the route; after the vehicle begins to overcome the route, and after the first estimate of fuel consumption, form a second estimate of fuel consumption for the remainder of the route; control the amount of fuel in the vehicle as the vehicle overcomes the route; make the second decision that the amount of fuel in the vehicle is not enough for the vehicle to reach the final destination of the route; and recommend an intermediate waypoint for refueling the vehicle.

In a further aspect, the computer is further configured to recommend an intermediate waypoint based on at least one of a vehicle driving history and user input regarding a preferred intermediate waypoint.

In another further aspect, the computer is further configured to estimate fuel costs for a route at least partially based on estimated fuel consumption.

In yet another further aspect, the estimated fuel consumption is based in part on comparing the collected data stored in the computer with the driver characteristics stored in the personalized hardware system.

In yet a further aspect, the computer is further configured to recommend an intermediate waypoint based on at least one of a vehicle driving history and user input regarding a preferred intermediate waypoint.

In yet a further aspect, the computer is further configured to use data received from a remote server to partially determine at least one of a first estimate of fuel consumption, a second estimate of fuel consumption, and an intermediate route point.

In yet a further aspect, at least one of the first estimate of fuel consumption and the second estimate of fuel consumption is based in part on collected computer data relating to at least one of weather, traffic, and construction conditions.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an exemplary vehicle system.

FIG. 2 is a diagram of an exemplary sequence of operations for forming and / or selecting a vehicle route.

FIG. 3 illustrates an example user interface for providing possible routes for selection by a user.

DETAILED DESCRIPTION

SYSTEM OVERVIEW

FIG. 1 is a block diagram of an exemplary system 100 for route planning with combined fuel costs and other data. The computing device 105 in the vehicle 101 as a whole includes a navigation module 106. In addition, computing device 105 typically receives user input and / or provides output to a user through a human-machine interface (HMI), and also receives and processes collected data 115 from one or more data collection devices, such as sensors. In addition, the computer 105 typically receives and / or stores parameters 116 as input, which, possibly along with the collected data 115, can be used by the navigation module 106 to form one or more routes for the vehicle 101. Alternatively or additionally, the module 106 navigation and other commands and / or data described in the materials of this application as executable or stored in the computer 105 may be included in the user device 150, such as a smartphone, or the like. Remote server 125 may also provide data, for example, retrieved from data storage 130, for use in navigation and / or route planning.

EXAMPLE SYSTEM ELEMENTS

A vehicle 101, for example, a car, a light truck, a medium truck or a heavy duty truck, an aircraft, a ship, etc., includes a vehicle computer 105, which typically includes a processor and memory , the memory includes one or more forms of computer-readable media and stores instructions executed by the processor to perform various operations, including those disclosed in the materials of this application. In addition, the computer 105 may include or be coupled to more than one computing device, such as controllers, or the like, included in the vehicle 101 for monitoring and / or controlling various components of the vehicle, for example, an engine control unit (ECU), transmission control unit (TCU), etc.

Computer 105 is generally configured to communicate on a local area network (CAN) bus or the like. Computer 105 may also be connected to an on-board diagnostic (OBD-II) connector. Through the CAN bus, OBD-II and / or other wired or wireless mechanisms, the computer 105 can transmit messages to various devices in the vehicle and / or receive messages from various devices, for example, controllers, actuators, sensors, etc., in including data collection devices 110. Alternatively or additionally, in the case where the computer 105 actually contains multiple devices, a CAN bus or the like can be used for communication between devices presented as the computer 105 in this disclosure.

In addition, the computer 105 may be configured to communicate with the network 120, which, as described below, may include various wired and / or wireless networking technologies, for example, cellular, Bluetooth, wired and / or wireless packet networks, etc. In addition, the computer 105 receives data, for example, from one or more data collection devices 110 and / or a human machine interface (HMI), such as an interactive voice response system (IVR), graphical user interface (GUI), including touch screen or the like, etc. The computer can also output signals, for example, to display a route or routes for the vehicle 101, to receive user input related to a route, route selection, etc.

In a general sense, the instructions stored in and executed by the computer 105 (either alternatively or additionally in the user device 150) comprise a navigation module 106. Using data received at computer 105, for example, from data collection devices 110, data included as stored parameters 116, and / or data from server 125, etc., module 106 can facilitate navigation, including including the formation of one or more routes and / or potential routes for the vehicle 101.

Data acquisition devices 110 may include a variety of devices. For example, various controllers in a vehicle may operate as data acquisition devices 110 to provide data 115 via a CAN bus, for example, data 115 relating to speed, vehicle acceleration, etc. In addition, sensors or the like, Global Positioning System (GPS) equipment, etc. could be included in the vehicle and configured as data collection devices 110 to provide data directly to computer 105, for example, via a wired or wireless connection. Data acquisition devices 110 could also include sensors or the like for detecting conditions outside the vehicle 101, for example, medium-range or long-range sensors. For example, sensor data acquisition devices 110 could include mechanisms such as a radar, laser locator, sonar, cameras, or other image input devices that could be activated to measure the distance between vehicle 101 and other vehicles or objects , to detect other vehicles or objects, and / or to detect road conditions, such as bends, bumps, slopes, bulges, changes in slope, etc. In addition, data acquisition devices 110 may include sensors internal to vehicle 101, such as accelerometers, temperature sensors, motion detectors, etc., for detecting movement or other conditions of vehicle 101.

The memory of computer 105 typically stores the collected data 115. The collected data 115 may include a variety of data collected in the vehicle 101 from the data collection devices 110. Examples of the collected data 115 are given above, and furthermore, the data 115 may further include data calculated therefrom by the computer 105. In general, the collected data 115 may include any data that may be collected by the data collection device 110 or calculated from such data. Accordingly, the collected data 115 could include a variety of data related to the operation and / or performance of the vehicle 101, as well as data related, in particular, related to the movement of the vehicle 101. For example, the collected data 115 could include data regarding speed, acceleration, covered routes, vehicle fuel consumption, etc.

The memory of computer 105 may additionally store one or more parameters 116. Parameter 116 may include user preferences for forming and / or choosing a route, for example, choose the fastest, choose the most economical, weights that must be given to factors, such as costs for fuel, travel time, etc., when forming and / or choosing a route, etc.

In addition, the collected data 115 and / or parameters 116 could include data collected from the user device 150, the remote source 160, or some other mechanisms. For example, parameters 116 could be determined from data collected from the HMI of computer 105 and / or user device 150, regarding user preferences, for example, regarding preferred places of interest, route preferences, etc. In addition, the collected data 115 could include data from biometric sensor data collection devices 110, for example, indicating the likely age, gender, etc., of the driver of the vehicle 101.

In addition, still collected data 115 could be issued from other subsystems of the vehicle 101, coupled with the possibility of exchanging data with the vehicle 101, such as hardware, including a processor and memory storing an embedded program personalized for the driver of the vehicle 101, for example , a security system that identifies a driver of a vehicle 110, for example, using biometric sensor data collection devices 110, using a system that and entifitsiruet driver according to the electronic key, etc., and that implements a certain operations and / or limitations in the vehicle 101 based on the identity of the driver. In addition, the collected data 116 could be used to generate parameters 116. For example, according to the identity of the driver, the vehicle 101 could be limited from traveling on certain roads, for example, motorways, from traveling after a certain time of day, etc .; one or more parameters 116 could be implemented to enforce such restrictions. In addition, still collected data 115 could be obtained from one or more remote locations 160, that is, computer 105 could communicate directly with remote location 160 and / or could receive collected data 115 from server 125, which server 125 received from a remote location 160, for example, fuel prices, current or predicted weather, etc.

In yet another example, the collected data 115 could include statistical and / or real time (or near real time) traffic data that is collected and stored on the server 125, for example, from remote locations 160, and delivered to the vehicle computer 105 101. Using such collected data 115, a computer, for example, could, in cases where it is determined that vehicle 101 is approaching an area of heavy traffic when traffic jams or the like are possible, recommend so that the vehicle 101 is refueling, visits intermediate points of the route with refueling, etc. Similarly, information related to road construction, such as closing roads, closing lanes, working on bridges, etc., which could cause traffic jams, detours, etc., could be generated.

The network 120 shown in FIG. 1, is one or more mechanisms by which vehicle computer 105 can communicate with a remote server 125 and / or user device 150. Accordingly, network 120 may be one or more of various wired or wireless communication mechanisms, including any desired a combination of wired (e.g., cable or fiber) and / or wireless (e.g., cellular, wireless, satellite, microwave or radio frequency) communication mechanisms and any desired topology with ti (or topologies when multiple communication mechanisms are used). Exemplary communications networks include wireless communications networks (eg, Bluetooth, IEEE 802.11, etc.), local area networks (LANs) and / or wide area networks (WANs), including the Internet, providing data services.

Server 125 may be one or more computer servers, each generally including at least one processor and at least one memory, the memory stores instructions executed by the processor, including instructions for performing the various steps and sequences of operations described in the materials of this application. Server 125 may include or be coupled to a data store 130 to store collected data 115 and / or parameters 116, for example, which could be downloaded from one or more computers 105 of the vehicle 101. For example, one or more parameters 116 for a particular user could be stored in the server 125 and retrieved by the computer 105 when the user was in a particular vehicle 101.

The user device 150 may be any one of a variety of computing devices including a processor and memory, as well as communication capabilities. For example, user device 150 may be a laptop computer, tablet computer, smartphone, etc., which includes wireless capabilities using IEEE 802.11, Bluetooth, and / or cellular protocols. In addition, user device 150 may use communication capabilities to maintain communication through network 120, including with vehicle computer 105. The user device 150 could communicate with the computer 105 of the vehicle 101, through other mechanisms, such as the network in the vehicle 101, known protocols, such as Bluetooth, etc. Accordingly, the user device 150 can be used to perform certain operations attributed to the data collection device 110 in the materials of this application, for example, speech recognition functions, cameras, global positioning system (GPS) functions, etc., could be used to provide data 115 to computer 105. In addition, user device 150 could be used to provide a human machine interface (HMI) to computer 105.

One or more remote locations 160 may be accessible by server 125 and / or computer 105 via network 120, such as the Internet. For example, the remote location 160 could be a social network or the like, issuing data 115 relating to preferred for drivers of vehicles 101 trademarks of a restaurant, fuel, etc., preferred routes and other personal attributes. In addition, the remote location may provide collected data 115, for example, for use in determining parameters 116, or which can be compared with parameters 116. For example, as mentioned above, the collected data 115 from the remote location 160 could indicate one or more gas stations in geographical area. Such collected data 115 could be compared with user parameters 116 defining a fuel preference for the user.

Sample Stream of Operation Sequence

FIG. 2 is a diagram of an example sequence of operations 200 for generating and / or selecting a route of a vehicle 101. The steps of a sequence of 200 operations are attributed to computer 105, but, as mentioned above, some or all of the steps of a sequence of operations 200 could alternatively or additionally be performed according instructions executed by user device 150.

The process 200 starts at the top 205 of the flowchart, where the computer 105 identifies the end points of the route for the route to be traveled by the vehicle 101. For example, the navigation module 106 may receive user input defining a route request between the starting point and the destination , or the final destination of the route.

In addition, the collected data 115 and / or parameters 116 can be extracted, for example, from the memory of computer 105 and / or server 125 and used to specify the starting points and end points of the routes. For example, parameters 116 may be stored according to daily commuting schemes or the like in the vehicle 101. For example, the vehicle 101 is subjected to power-up at a particular time of day and / or day of the week as indicated by the clock supported by computer 105, and then used to movement from a given starting point to a given destination, computer 105 may, after this pattern is repeated a predetermined number of times, save a parameter or parameters 115 indicating that the default navigation module 106 should assume the data starting and ending points of the route. Similarly, computer 105 could store previous routes traveled one or more times in vehicle 101 as parameters 116, and then based on collected data 115 showing that vehicle 101 is traveling one of these previous routes, could retrieve parameters 116 starting and ending points for the current route of the vehicle 101 based on such previous routes. Similarly, parameter 116 could set the end point of the route simply from the collected data 115, showing the current location, for example, the starting point of the route, of the vehicle 101.

Then, at the top 210 of the flowchart, computer 105 identifies the intermediate route points for the route of the vehicle 101. For example, a user input could be received defining intermediate route points to be traveled between the starting point and the destination of the route, for example, the user could prescribe identify restaurants, gas stations, restrooms, convenience stores, etc. between the starting point of the route and the final point of the route. In addition, for example, one or more intermediate points of the route could be inferred from parameters 116, for example, vehicle 101 invariably visits a specific one in the city during a morning trip to work in the city, parameter 116, therefore, identifies the location of the house.

Similarly, for example, in cases where the starting point and the final point were at some distance, such that refueling may be required to reach the destination, in cases where the collected data 115 indicate that the fuel level in the vehicle 101 is lower a certain threshold value, for example, less than half the tank, etc., the refueling location between the starting point and the final point could be extracted from the data stored by the navigation module 106. In addition, such refueling locations could be selected according to parameters 116, for example, parameters 116 may store the user's preference for the fuel trademark and / or may prescribe that the user simply desires the cheapest possible refueling option. In addition, the intermediate waypoints with a gas station could be selected according to the fuel prices associated with the respective intermediate waypoints. For example, current average fuel prices for gas stations in a specific geographic area, within a predetermined distance, such as Ѕ miles, route, etc. could be retrieved by computer 105 from server 125 on a periodic basis, based on almost real time or real time, as a result of which computer 105 could select intermediate route points with refueling according to the lowest fuel prices, for example, display only the lowest 10%, 25 %, etc. In addition, when an intermediate route point is displayed with refueling, for example, represented by an icon or the like, with reference to the route, the average or characteristic fuel price associated with the intermediate route point could also be displayed.

In addition, intermediate route points could be selected based on an association with each other. For example, if computer 105 determines that the intermediate points of the refueling route should be provided by the route, the intermediate points of the refueling route could be selected according to their proximity to other intermediate points of the route. For example, parameter 116 could set the user's preference for a particular restaurant chain, as a result of which only gas stations within a predetermined distance, for example, ј miles, from the restaurant’s location on the network would appear as intermediate points of the route. Alternatively or additionally, the user could provide input via the HMI of the vehicle 101 to request a search for restaurants in the vicinity of the route. To identify the need for refueling, computer 105 could only select intermediate points of the route with fuel that are located near, for example, at the same exit from the motorway as the intermediate point of the route with the restaurant, to maximize the efficiency of the trip and minimize the total trip time .

Then, at the top 215 of the flowchart, computer 105 determines whether a fuel-related threshold value has been triggered on the vehicle 101. For example, as mentioned in the previous paragraph, computer 105 can detect whether the fuel level in the vehicle 101 is below a certain threshold value, for example , half tank, quarter tank, etc. In addition, the fuel level in the vehicle 101 may be taken into account as the only collected data 115 or in combination with one or more elements of the collected data 115, for example, the distance between the starting point and the final point on the route, calculating the likely fuel consumption to overcome the route from the starting point to the final point and determining whether refueling is required to reach the destination. In this example, if the calculation determined that a refueling would probably be required to reach the destination, then a fuel-related threshold would be triggered. Moreover, a fuel-related threshold could be triggered in cases where the user provided input that the vehicle 101 should refuel at a specific time before reaching a specific destination or waypoint, etc.

In any case, if a fuel-related threshold value is triggered, then vertex 220 of the flowchart is executed next. Otherwise, the sequence of operations 200 goes to the top 225 of the flowchart.

At top 220 of the flowchart, computer 105 retrieves and / or updates the refueling data stored as parameters 116. As explained above, top 220 of the flowchart is executed when it has been determined that refueling is required or necessary at route between given destination points. Accordingly, the computer 105 retrieves one or more possible intermediate points of the route with fuel refueling, which could be identified above, as described with reference to the top 210 of the flowchart, and also retrieves data indicating fuel costs, for example, price per gallon for type the fuel used by the vehicle 101, the price of recharging the batteries used to fuel the vehicle 101, etc., associated with each respective intermediate points m rshruta with refueling. Such data may be retrieved in real time or near real time from server 125 and / or may be periodically updated from server 125 and / or some other source.

Following vertex 215 of the flowchart or vertex 220 of the flowchart at vertex 225 of the flowchart, computer 105 generates one or more possible routes for vehicle 101 between predetermined end points. For example, in a known manner according to various criteria, for example, the shortest distance between given endpoints, the shortest time to overcome given endpoints, use only main roads or highways, avoid main highways, etc. In addition, computer 105 could take into account various intermediate route points between predetermined endpoints, for example, computer 105 could provide a first route that includes a specific intermediate route point, and a second route that does not include an intermediate route point.

Then, at top 230 of the flowchart for each route formed at top 225 of the flowchart, computer 105 calculates estimated fuel costs to overcome the route, and can also identify gas stations and other intermediate route points that may be associated with the route.

In general, for each route formed at the top 225 of the flowchart, estimated fuel costs for the route can be calculated, for example, parameter 116 could include the average price paid for a certain amount, for example, per gallon, of fuel for a vehicle 101 Alternatively, the average estimated fueling price could be calculated from the stored fueling data, as described above with reference to the top 220 of the flowchart.

In addition, parameters 116 could indicate the expected fuel consumption rate, for example, in miles per gallon, the consumption of the electric battery, etc., for the vehicle 101. The expected fuel consumption rate could be accumulated from the available information for a particular type, power transmission etc. Vehicle 101 provided by a government agency or third party, such as the Environmental Protection Agency. Alternatively, computer 105 could calculate the expected fuel consumption rate based on the collected data 115, including the amount of fuel spent on previous trips covering given distances, given types of roads on the ground, etc.

Using the expected fuel consumption rate, the expected average price to be paid for the fuel, and distance, type of terrain, type of road, etc. For a given route, estimated fuel costs for the route can be calculated. In addition, other factors may be considered. For example, the computer 105 could receive from the server 125 or from some other source, such as a remote location 160, data related to current weather conditions, traffic conditions, construction conditions, etc. Accordingly, situations where the expected fuel consumption rate could be influenced by traffic, for example, be higher than normal due to slow traffic conditions or weather, for example, be lower than normal, due to strong tailwind, the expected flow rate fuel, and from here, the expected fuel costs to overcome the route could be adjusted appropriately.

In addition, as mentioned above, the top 230 of the flowchart may include identification of intermediate route points that may be included in a particular route. For example, a user could stipulate a desire to stay in a restaurant between specified destination points, as a result of which computer 105 can identify intermediate route points at or within a specified distance, for example, one mile, five miles, etc. this route. Similarly, computer 105 can identify gas stations along a given route, and can also optionally indicate the likely cost of refueling, such as the price per gallon of fuel, the price of electricity, etc., associated with one or more of these gas stations. Intermediate points of the route, including intermediate points of the route with refueling, can be identified by computer 105, as described above with respect to vertex 210 of the flowchart, and then selected for inclusion in the composition or to be provided along with a specific route, as described at this vertex 230 flowcharts.

Following the top 230 of the flowchart at the top 235 of the flowchart, computer 105 selects a route from the routes formed at the top 225 of the flowchart. The route selection may occur according to user input and / or one or more parameters 116. For example, computer 105 may receive user input indicating a route to be selected. FIG. 3 illustrates an example user interface 300 for providing possible routes for selection by a user. In the example of FIG. 3, the user is provided with a first route and a second route between two end points for selection. In addition, the interface 300 provides information including an estimated time to overcome each of the routes, as well as estimated fuel costs for each of the two routes. As can be seen, the interface 300 also provides information about the various intermediate points of the route on each of the two routes in the form of pictograms representing possible intermediate points of the route, for example, gas stations, antique shops, picturesque areas and restaurants. In this example, the first route has a lower travel time but higher fuel costs than the second route. As noted above, various factors can affect fuel costs, including traffic, weather, the likely cost of fuel along the route, etc. In any case, the interface 300 would allow the user to choose between two routes.

Moreover, as mentioned above, computer 105 could include commands for selecting a route without user input. For example, computer 105 could be configured, for example, according to parameter 116 provided by the previous user input, to invariably choose a route with the shortest travel time, always choose a route with lower fuel costs, closer to a particular network of gas stations, restaurants, recreation areas etc.

After the route is selected, as described with reference to the top 235 of the flowchart, and the vehicle 101 begins to overcome the route, at the top 240 of the flowchart, the computer 105 determines whether the route should be modified to add new waypoints. For example, a user may provide input requesting the location of a restaurant, retail store, gas station, etc. on the route.

In addition, the computer 105 could be configured to issue warnings in response to which the user could select a new waypoint. For example, during or before the refueling process, computer 105 could detect that the vehicle 101 was at a particular gas station, and could additionally determine that the less expensive gas station was within a predetermined distance from the selected route, for example, ½ mile, 1 mile, 5 miles, etc., and could be reached on the amount of fuel remaining in the vehicle 101. Computer 105, in addition, could give the user a choice to add a less expensive gas station tion as an intermediate point of the route.

In any case, if input has been received to add an intermediate waypoint, or otherwise determined that an intermediate waypoint should be added, then the sequence of 200 operations returns to the top 215 of the flowchart, as a result of which the route selected at the top 235 of the flowchart can be modified as follows, for example, according to the steps of the sequence of operations 200 discussed above. Otherwise, the flow goes to the top 245 of the flowchart.

At top 245 of the flowchart, computer 105 determines whether a fuel-related threshold value has been triggered. For example, as mentioned above, the computer 105 could be configured to determine when the fuel level in the vehicle 101 fell below a certain threshold value, when the vehicle 101 would probably need to refuel before reaching its destination, etc. If a fuel-related threshold value has been triggered, then the process 200 returns to the top 220 of the flowchart, whereby, as discussed above with reference to the top 220 of the flowchart and subsequent vertices of the flowchart, new route or routes could be formed, including intermediate route points to meet the needs of refueling the vehicle 101 and / or to enable the vehicle 101 to reach the desired destination without refueling. Otherwise, the flow 200 proceeds to the top 250 of the flowchart. As noted below, the sequences of operations discussed in the materials of this application could include other steps or steps performed in a different order than those disclosed in the materials of this application. For example, the top 245 of the flowchart could run earlier than the top 240 of the flowchart.

At top 250 of the flowchart, computer 105 determines whether a sequence of 200 operations will continue. For example, if the destination is reached, the vehicle 101 is de-energized, etc., then the process 200 may end. If the sequence of operations 200 should not continue, then the sequence of 200 operations ends after the top 250 of the flowchart. Otherwise, the sequence of operations 200 returns to the top 215 of the flowchart.

CONCLUSION

Computing devices, such as those discussed herein, each typically includes instructions executed by one or more computing devices, such as those identified above, and for executing vertices of flowcharts or steps of the process sequences described above. For example, the vertices of the flowcharts discussed above can be embodied as computer-executable instructions.

Machine-executable instructions can be compiled or interpreted from computer programs created using a variety of languages and / or programming technologies, including, but not limited to, and alone or in combination, Java, C, C ++, Visual Basic, Java Script, Perl, HTML, etc. In general, a processor (e.g., a microprocessor) receives instructions, for example, from memory, a computer-readable medium, etc., and executes these instructions, thereby performing one or more sequences of operations, including one or more of the sequences of operations described in the materials of this application. Such commands and other data may be stored and transmitted using a variety of computer-readable media. A file in a computing device is typically a collection of data stored on a computer-readable medium, such as a storage medium, random access memory, etc.

A machine-readable medium includes any medium that is involved in providing data (e.g., instructions) that can be read by a computer. Such a medium can take many forms, including, but not limited to, non-volatile media, volatile media, etc. Non-volatile media, for example, include optical or magnetic disks and other read-only memory. Volatile media includes dynamic random access memory (DRAM), which typically constitutes main memory. Common forms of computer-readable media, for example, include a floppy disk, floppy disk, hard disk, magnetic tape, any other magnetic medium, CD-ROM (read-only memory (ROM) on a CD), DVD (digital multifunction disk), any other optical media, punched cards, paper tape, any other physical media with hole patterns, RAM (random access memory, RAM), EPROM (programmable ROM, PROM), EPROM (erasable programmable ROM, EPROM), flash memory / EEPROM ( FLASH-EEPROM (Electrically TYRA Programmable ROM)), any other memory chip or cartridge or any other medium from which a computer can perform the reading.

In the drawings, like reference numbers indicate identical elements. In addition, some or all of these elements could be changed. As for the environments, sequences of operations, systems, methods, etc. described in the materials of this application, it should be clear that although the steps of such sequences of operations, etc. were described as occurring according to a certain ordered sequence, such sequences of operations could be carried out in practice with the described steps performed in a different order than the order described in the materials of this application. In addition, it should be understood that some steps could be carried out simultaneously, that other steps could be added, or that some steps described in the materials of this application could be omitted. In other words, the method descriptions in the materials of this application are provided to illustrate some embodiments and should not be construed in any way in order to limit the claimed utility model.

Accordingly, it should be understood that the foregoing description is intended to be illustrative and not restrictive. Many embodiments and applications other than the provided examples would be apparent to those skilled in the art upon reading the above description. The volume of the utility model should not be determined with reference to the above description, but instead should be determined with reference to the attached formula of the utility model along with the full amount of equivalents to which such a formula of the utility model is entitled. It is expected and implied that future improvements will occur in the areas of technology discussed in the materials of this application, and that the disclosed systems and methods will be embodied in such future embodiments. Summarizing the above, it should be clear that the utility model is modifiable and changeable and is limited solely by the following utility model formula.

All terms used in the utility model formula are implied by their most free expansive interpretations and their usual meanings as understood by those skilled in the art, unless explicitly stated otherwise in the materials of this application. In particular, the use of the singular, “mentioned”, etc. shall be read outlining one or more of the indicated elements, unless the claim of the utility model formula expresses an explicit limitation to others.

Claims (20)

1. A device for planning the route of a vehicle taking into account fuel, comprising a computer on a vehicle, the computer comprising a processor and memory, wherein the computer is configured to: determine the estimated fuel consumption for the route for the vehicle; determine, at least in part, based on the estimated fuel consumption, that the amount of fuel in the vehicle is not enough for the vehicle to travel the route; and recommend one or more intermediate route points within a predetermined distance of the route for refueling the vehicle. 2. The device of claim 1, wherein the computer is further configured to estimate fuel costs for the route at least partially based on estimated fuel consumption. 3. The device according to claim 1, in which the estimated fuel consumption is based in part on comparing the collected data stored in the computer with the characteristics of the driver stored in the personalized hardware system. 4. The device according to claim 1, in which the estimated fuel consumption is based in part on collected data stored on a computer related to at least one of: weather conditions, traffic conditions and construction conditions. 5. The device according to claim 1, wherein the computer is further configured to recommend an intermediate waypoint based on at least one of a vehicle driving history and user input regarding a preferred intermediate waypoint.             6. The device according to claim 1, wherein the computer is further configured to use data received from a remote server, partially to determine at least one of the estimated fuel consumption and one or more intermediate points of the route. 7. The device according to p. 1, in which the computer is additionally configured to use the data received using the driver input into the computer, partially to recommend one or more intermediate points of the route. 8. The device according to claim 1, in which the computer is additionally configured to: form at least a second route between the starting point and the final point; and present each of the route and the second route for selection on the human-machine interface along with estimated fuel costs for each of the route and the second route. 9. A device for planning a route of a vehicle taking into account fuel, comprising a computer on a vehicle, the computer comprising a processor and memory, the computer being configured to: identify the starting point and destination of the vehicle; form at least a first route and a second route between the starting point and the final point; determine, for each of the first route and the second route, the estimated fuel consumption for the vehicle; and issue each of the first route and the second route for selection on the human-machine interface, which also displays the estimated fuel costs for each of the first route and the second route. 10. The device according to claim 9, in which the estimated fuel consumption for at least one of the first route and the second route is based in part on comparing the collected data stored in the computer with the driver characteristics stored in the personalized hardware system. 11. The device according to claim 9, in which the estimated fuel consumption for at least one of the first route and the second route is based in part on collected data stored in a computer related to at least one of weather conditions, traffic conditions and construction conditions . 12. The device according to claim 9, in which the computer is further configured to recommend an intermediate waypoint for at least one of the first route and the second route based on at least one of the vehicle’s driving history and user input regarding the preferred intermediate waypoint. 13. The device according to p. 9, in which the computer is additionally configured to use data received from a remote server, partially to determine at least one of the estimated fuel consumption, the first route and the second route. 14. A device for planning a route of a vehicle taking into account fuel, comprising a computer on a vehicle, the computer comprising a processor and memory, wherein the computer is configured to: identify the starting point and destination of the vehicle; form a route between the starting point and the final point; generate the first estimated fuel consumption for the route; make the first decision, at least in part based on the estimated fuel consumption, that the amount of fuel in the vehicle is sufficient for the vehicle to travel the route; after the vehicle began to overcome the route, and after the first estimate of fuel consumption, form a second estimate of fuel consumption for the remainder of the route; control the amount of fuel in the vehicle as the vehicle overcomes the route; make the second decision that the amount of fuel in the vehicle is not enough for the vehicle to reach the final destination of the route; and recommend an intermediate waypoint for refueling a vehicle. 15. The device according to claim 14, wherein the computer is further configured to recommend an intermediate waypoint based on at least one of a vehicle driving history and user input regarding a preferred intermediate waypoint. 16. The device according to p. 14, in which the computer is additionally configured to estimate fuel costs for the route at least partially based on the estimated fuel consumption. 17. The device according to claim 14, in which the estimated fuel consumption is based in part on comparing the collected data stored in the computer with the driver characteristics stored in the personalized hardware system. 18. The device of claim 14, wherein the computer is further configured to recommend an intermediate waypoint based on at least one of a vehicle driving history and user input regarding a preferred intermediate waypoint. 19. The device according to p. 14, in which the computer is additionally configured to use data received from a remote server, partially to determine at least one of the first estimate of fuel consumption, the second estimate of fuel consumption and an intermediate route point. 20. The device according to p. 14, in which at least one of the first estimate of fuel consumption and the second estimate of fuel consumption is based in part on collected data stored in a computer related to at least one of weather conditions, traffic conditions and construction conditions .

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