cooperative navigation

Abstract

This disclosure provides "cooperative navigation". Multiple routes from origin to destination are received from each of a plurality of navigation applications executed by one or more controllers and / or by one or more mobile devices communicating with the vehicle via at least one connectivity interface. Recommended routes are identified from each of the plurality of navigation applications to define a set of recommended routes. The recommended routes are aggregated to determine differences between them. In response to consistency among the recommended routes, the recommended routes are used as the optimized route for the vehicle. In response to inconsistencies among the recommended routes, the differences are displayed in the vehicle's HMI.

Description

Technical Field

[0001] The various aspects disclosed herein generally relate to navigation and route planning. Background Technology

[0002] Navigation systems exist in many forms. Some are integrated into vehicles, while others are provided via mobile devices. Different navigation systems may have different features and / or may provide different guidance to users. Summary of the Invention

[0003] In one or more illustrative examples, a vehicle for determining an optimal route includes: one or more controllers providing at least one connectivity interface configured to connect to a plurality of navigation applications executed by the one or more controllers and / or by one or more mobile devices; and a navigation engine executed by at least one of the one or more controllers, the navigation engine being configured to: receive multiple routes from origin to destination from each of the plurality of navigation applications, including identifying recommended routes from each of the plurality of navigation applications to define a set of recommended routes, aggregating the recommended routes to determine differences between the recommended routes, utilizing the recommended routes as optimized routes for the vehicle in response to consistency of the recommended routes, and displaying the differences in the vehicle's human-machine interface (HMI) in response to inconsistency of the recommended routes.

[0004] In one or more illustrative examples, the at least one connectivity interface includes a plurality of connectivity interfaces, and the one or more controllers providing the plurality of connectivity interfaces include at least two of a telematics control unit (TCU), a vehicle entertainment controller, and a keyless entry controller.

[0005] In one or more illustrative examples, a first navigation application among the plurality of navigation applications is executed by a first mobile device among the one or more mobile devices, and a second navigation application among the plurality of navigation applications is executed by a second mobile device among the one or more mobile devices.

[0006] In one or more illustrative examples, the plurality of navigation applications include a plurality of navigation applications executed by one of the one or more mobile devices.

[0007] In one or more illustrative examples, a first navigation application among the plurality of navigation applications is executed by the one or more controllers, and a second navigation application among the plurality of navigation applications is executed by a first mobile device among the one or more mobile devices.

[0008] In one or more illustrative examples, the navigation engine is also configured to use one or more weather applications executed by the one or more mobile devices to retrieve weather conditions associated with the multiple routes; and to optimize the recommended routes based on user-defined weather preferences and the retrieved weather conditions.

[0009] In one or more illustrative examples, in response to all routes in the recommended routes changing within a predefined time threshold, the navigation engine determines the recommended routes to be consistent.

[0010] In one or more illustrative examples, in response to the majority of the recommended routes being consistent, the navigation engine determines the recommended routes to be consistent.

[0011] In one or more illustrative examples, the navigation engine is further configured to receive first traffic-related route conditions from a first navigation application among the plurality of navigation applications; receive second traffic-related route conditions from a second navigation application among the plurality of navigation applications; utilize a machine learning model to determine whether the first and second traffic-related route conditions confirm a problem along the optimized route; in response to the first and second traffic-related route conditions indicating a confirmed problem, display the confirmed problem in the HMI as identified by the first and second navigation applications; and otherwise, display the first and second traffic-related route conditions as separate problems in the HMI.

[0012] In one or more illustrative examples, the navigation engine is also configured to send a message to a crowdsourcing data monitoring device to request crowdsourcing data; and to receive the crowdsourcing data from the crowdsourcing data device to verify and / or supplement the traffic-related route conditions from the navigation application.

[0013] In one or more illustrative examples, a method for determining an optimal route for a vehicle includes: receiving multiple routes from a point of origin to a destination from each of a plurality of navigation applications executed by the one or more controllers and / or by one or more mobile devices communicating with the vehicle via at least one connectivity interface; identifying recommended routes from each of the plurality of navigation applications to define a set of recommended routes; aggregating the recommended routes to determine differences between the recommended routes; utilizing the recommended routes as the optimized route for the vehicle in response to agreement between the recommended routes; and displaying the differences in the vehicle's HMI in response to disagreement between the recommended routes.

[0014] In one or more illustrative examples, the method further includes providing a plurality of connectivity interfaces using at least two of the vehicle's TCU, the vehicle's infotainment controller, and the vehicle's keyless entry controller, wherein a first navigation application among the plurality of navigation applications is executed by a first mobile device among the one or more mobile devices, and wherein a second navigation application among the plurality of navigation applications is executed by a second mobile device among the one or more mobile devices.

[0015] In one or more illustrative examples, the method further includes using one or more weather applications executed by the one or more mobile devices to retrieve weather conditions associated with the plurality of routes; and optimizing the recommended routes based on user-defined weather preferences and the retrieved weather conditions.

[0016] In one or more illustrative examples, the method further includes determining the recommended routes as consistent in response to all routes in the recommended routes changing within a predefined time threshold; or determining the recommended routes as consistent in response to most routes in the recommended routes being consistent.

[0017] In one or more illustrative examples, the method further includes receiving a first traffic-related route condition from a first navigation application among the plurality of navigation applications; receiving a second traffic-related route condition from a second navigation application among the plurality of navigation applications; using a machine learning model to determine whether the first traffic-related route condition and the second traffic-related route condition confirm a problem along the optimized route; in response to the first traffic-related route condition and the second traffic-related route condition indicating a confirmed problem, displaying the confirmed problem in the HMI as identified by the first navigation application and the second navigation application; and otherwise, displaying the first traffic-related route condition and the second traffic-related route condition as separate problems in the HMI.

[0018] In one or more illustrative examples, the method further includes sending a message to a crowdsourcing data monitoring device to request crowdsourcing data; and receiving the crowdsourcing data from the crowdsourcing data device to verify and / or supplement the traffic-related route conditions from the navigation application.

[0019] In one or more illustrative examples, a non-transitory computer-readable medium includes instructions for determining an optimal route for a vehicle, which, when executed by one or more controllers of the vehicle, cause the vehicle to perform operations including: providing multiple connectivity interfaces using at least two of the vehicle's TCU, the vehicle's infotainment controller, and the vehicle's keyless entry controller; receiving multiple routes from origin to destination from each of multiple navigation applications executed by the one or more controllers and / or by multiple mobile devices communicating with the vehicle through the multiple connectivity interfaces; identifying recommended routes from each of the multiple navigation applications to define a set of recommended routes; aggregating the recommended routes to determine differences between the recommended routes; utilizing the recommended routes as the optimized route for the vehicle in response to agreement between the recommended routes; and displaying the differences in the vehicle's HMI in response to disagreement between the recommended routes.

[0020] In one or more illustrative examples, the non-transitory computer-readable medium also includes instructions, when executed by one or more controllers of the vehicle, to cause the vehicle to perform operations including: using one or more weather applications executed by the plurality of mobile devices to retrieve weather conditions associated with the plurality of routes; and optimizing the recommended routes based on user-defined weather preferences and the retrieved weather conditions.

[0021] In one or more illustrative examples, the non-transitory computer-readable medium also includes instructions, when executed by one or more controllers of the vehicle, to cause the vehicle to perform the following operation: determining the recommended route as consistent in response to at least a majority consistency of the recommended route.

[0022] In one or more illustrative examples, the non-transitory computer-readable medium further includes instructions, when executed by one or more controllers of the vehicle, to cause the vehicle to perform operations including: receiving a first traffic-related route condition from a first navigation application among the plurality of navigation applications; receiving a second traffic-related route condition from a second navigation application among the plurality of navigation applications; using a machine learning model to determine whether the first traffic-related route condition and the second traffic-related route condition confirm a problem along the optimized route; in response to the first traffic-related route condition and the second traffic-related route condition indicating a confirmed problem, displaying the confirmed problem in the HMI as identified by the first navigation application and the second navigation application; and otherwise, displaying the first traffic-related route condition and the second traffic-related route condition as separate problems in the HMI.

[0023] In one or more illustrative examples, the non-transitory computer-readable medium also includes instructions, when executed by one or more controllers of the vehicle, to cause the vehicle to perform operations including: sending a message to a crowdsourcing data monitoring device to request crowdsourcing data; and receiving the crowdsourcing data from the crowdsourcing data device to verify and / or supplement the traffic-related route conditions from the navigation application. Attached Figure Description

[0024] Figure 1 An exemplary navigation system for determining the optimal route selection for a vehicle is shown;

[0025] Figure 2A An exemplary navigation application overlay map is shown, illustrating multiple routes between the origin and destination as determined by a first navigation application;

[0026] Figure 2B Another exemplary navigation application overlay map is shown, illustrating multiple routes between the origin and destination as determined by a second navigation application;

[0027] Figure 2C This illustrates yet another exemplary navigation application overlay map showing multiple routes between origin and destination, as determined by a third navigation application.

[0028] Figure 2D An example of a human-machine interface that displays warning images for traffic-related issues in a navigation application is shown;

[0029] Figure 2E An example of a human-machine interface is shown that displays multiple images and warnings for traffic-related issues from a first navigation app, a second navigation app, a third navigation app, and a weather alert from a weather-related app;

[0030] Figure 3 An exemplary process is shown for providing an optimized navigation route to a destination using a navigation engine that communicates with multiple navigation and / or weather applications;

[0031] Figure 4 An exemplary process is shown for providing notifications of traffic-related and / or weather-related issues using a navigation engine that communicates with multiple navigation and / or weather applications;

[0032] Figure 5 An illustrative example is shown of a vehicle using crowdsourced data to validate and / or augment the operation of its navigation engine; and

[0033] Figure 6 An exemplary computing device is shown for implementing a navigation system for determining the optimal route selection for a vehicle. Detailed Implementation

[0034] This document describes embodiments of the present disclosure. However, it should be understood that the disclosed embodiments are merely examples, and other embodiments may take various forms and alternative forms. The drawings are not necessarily drawn to scale; some features may be enlarged or minimized to show details of specific components. Therefore, the specific structural and functional details disclosed herein are not to be construed as limiting, but only as intended to teach those skilled in the art to adopt a representative basis of the invention in various ways. As will be understood by those skilled in the art, various features shown and described with reference to any of the drawings may be combined with features shown in one or more other drawings to produce embodiments not explicitly shown or described. The combinations of features shown provide representative embodiments for typical applications. However, for a particular application or implementation, various combinations and modifications of features consistent with the teachings of this disclosure may be desired.

[0035] Different navigation apps may offer different recommended routes to a destination or the same route with different time estimates. Users may question the accuracy of the recommended routes when arrival times and / or route recommendations change. Furthermore, different vehicle occupants may have different weather requirements. For example, a user hauling mud or mulch may not want to drive in the rain. In another example, an adventurer might prefer routes with snowy conditions to drive in snow.

[0036] The improved vehicle navigation method can be based on routes from multiple navigation applications and optionally take real-time weather into account. This method allows occupants to select routes with greater accuracy, taking into account their weather preferences.

[0037] The method can utilize multiple navigation applications simultaneously. In one example, a mobile device can simultaneously run multiple map-making programs (e.g., Waze, Apple Maps, Google Maps) and one or more weather-tracking programs (e.g., Weather Channel, Underground Weather Station, AccuWeather). In another example, multiple mobile devices can be connected to a vehicle, with each mobile device running one or more different navigation applications. Vehicle occupants can also stream music from one phone, navigation from another, and a weather application from yet another, for example, where different occupant devices may be responsible for these different tasks.

[0038] These multiple connections can be supported by multiple Bluetooth Low Energy (BLE) transceivers in the vehicle. For example, a first mobile device can connect to the connectivity interface of the vehicle's infotainment system, a second mobile device can connect to the connectivity interface of the telematics control unit (TCU), and a third mobile device can connect to the connectivity interface of the vehicle's Bluetooth access controller.

[0039] Vehicle occupants (also referred to as users in this document) can define a data source mapping for a combination of weather and navigation applications used by the vehicle. The vehicle can use a recommendation provided by the application if it offers a consistent recommendation. The vehicle can provide a majority vote or intervene to make a decision if the application provides differing results.

[0040] If the application is inconsistent and the vehicle occupants choose to intervene, they can choose a location to pull over and view the data. If autonomous operation is available, the vehicle can allow the user to view the information while moving, or allow passengers to view the data and choose the direction to follow.

[0041] The method can also combine traffic-related and / or weather-related route information from different applications to provide passengers with a unified information interface. To avoid redundancy, artificial intelligence (AI) techniques can be used to compare information from different applications to determine whether they are reporting the same or different issues. This can be beneficial because various applications may express the same information in different ways.

[0042] Furthermore, the architecture can leverage crowdsourced data from various sources, such as other vehicles, bystander mobile devices, and / or vehicle cameras. To incentivize the use of crowdsourced data, the method can offer rewards for route surveys and providing alternative route suggestions. Further aspects of this disclosure are discussed in detail herein.

[0043] Figure 1 An exemplary navigation system 100 for determining the optimal route selection for vehicle 102 is shown. Vehicle 102 may include various controllers 104. These controllers 104 may include a TCU 114 configured to communicate via a communication network 112, a vehicle entertainment controller (VEC) 116, a keyless entry controller (KEC) 118, and a Global Navigation Satellite System (GNSS) controller 108. Vehicle 102 may include additional hardware such as a human-machine interface (HMI) 120 and various sensors 106. In addition to vehicle 102, navigation system 100 includes at least one mobile device 110 communicating with vehicle 102. Mobile device 110 may be configured to execute navigation application 132 to determine route 122 using navigation application server 134, and may also be configured to execute weather application 136 to determine weather conditions 142 from weather application server 138. Navigation engine 140 may be executed by the controllers 104 of vehicle 102 to perform the optimized route selection discussed in detail herein. It should be noted that the navigation system 100 is only an example, and navigation systems 100 with more, fewer, or different components can be used.

[0044] Vehicle 102 may include multiple controllers 104 configured to perform and manage various vehicle 102 functions under the power of a vehicle battery and / or drivetrain. Vehicle controllers 104 may be discrete controllers 104. In other cases, controllers 104 may share physical hardware, firmware, and / or software, such that functions from multiple controllers 104 can be integrated into a single controller 104, and the functions of various such controllers 104 can be distributed across multiple controllers 104. Controllers 104 may be configured to communicate with each other via one or more vehicle buses. Vehicle buses may be configured to provide electrical interfaces between components of vehicle 102. As some non-limiting examples, vehicle buses may include one or more of a Controller Area Network (CAN), an Ethernet network, a Media-Oriented System Transport (MOST) network, and a wireless communication network.

[0045] Sensor 106 may include various hardware of vehicle 102 for collecting information about its surrounding environment and state. As some non-limiting examples, sensor 106 may include one or more of a camera (e.g., an advanced driver assistance system (ADAS) camera), an ultrasonic transceiver, a radio detection and ranging (radar) system, and / or a light detection and ranging (LiDAR) system.

[0046] The GNSS controller 108 can be configured to provide information indicating the current position of the vehicle 102. In one example, the GNSS controller 108 can be responsible for receiving signals from a GNSS constellation. This allows the GNSS controller 108 to receive time information and to determine the precise position of the vehicle 102. The position determined by the GNSS controller 108 can be used for various tasks, such as navigation or other location-based services.

[0047] Mobile device 110 may include mobile phones, tablet computers, laptop computers, and other portable electronic devices that can be carried by a user and configured to communicate wirelessly via communication network 112. Vehicle 102 may be configured to communicate with any of at least one of the mobile devices 110 using various communication protocols such as Bluetooth, Ultra-Wideband (UWB), Wi-Fi, or others.

[0048] Communication network 112 can provide communication services, such as packet-switched network services (e.g., Internet access, Voice over Internet Protocol (VoIP) communication services), to devices connected to it. As some non-limiting examples, communication network 112 may include one or more interconnected communication networks, such as the Internet, cable television distribution networks, satellite link networks, local area networks, vehicle-to-the-world (V2X) networks, dedicated short-range communication (DSRC) networks, and telephone networks.

[0049] TCU 114 is a controller 104 of vehicle 102 that can communicate via communication network 112. In one example, TCU 114 may be configured to provide network functionality to support telematics and / or autonomous driving services of vehicle 102. TCU 114 may include network hardware configured to facilitate communication between vehicle 102 and other devices of navigation system 100. For example, TCU 114 may include a cellular modem or otherwise access a cellular modem configured to facilitate communication with communication network 112. In some cases, TCU 114 may also support a connection to mobile device 110 as an additional or alternative communication channel between vehicle 102 and other devices.

[0050] The vehicle entertainment controller 116 is a controller 104 configured to support voice commands and Bluetooth interfaces with multiple mobile devices 110 (e.g., mobile devices 110A, 110B, 110C as shown), receive occupant input via various buttons or other controls, and provide navigation and weather information via HMI 120. The vehicle entertainment controller 116 may also support connections with the mobile devices 110 as a communication channel between the vehicle 102 and other devices.

[0051] KEC 118 is controller 104 and / or other hardware configured to provide keyless entry and / or occupant sensing capabilities to vehicle 102. KEC 118 may include a UWB transceiver, Bluetooth or Bluetooth Low Energy (BLEM) transceiver, or other network adapters that allow tracking of the location and / or identity of mobile device 110. KEC 118 may also support connectivity with mobile device 110 as a communication channel between vehicle 102 and other devices.

[0052] HMI 120 can be configured to provide an interface through which occupants of vehicle 102 can interact with vehicle 102. This interface may include controller 104, a touchscreen display, voice commands, and physical controls (such as buttons and knobs). HMI 120 can be configured to receive occupant input via various buttons or other controls, and to provide occupants with status information, such as fuel level information, engine operating temperature information, and the current location of vehicle 102. For example, HMI 120 can be configured to receive user input and display various elements discussed in detail herein, such as route 122, origin 124, destination 126, route selection preference 128, and weather preference 130. HMI 120 can be configured to provide information to various displays within vehicle 102, such as a center console touchscreen, instrument cluster screen, etc. HMI 120 can accordingly allow occupants of vehicle 102 to access and control various systems, such as navigation, entertainment, and communication systems, and climate controls.

[0053] Route 122 refers to the path that vehicle 102 can traverse from origin 124 to destination 126. Origin 124 refers to the starting position of route 122. In many examples, origin 124 is the current position of vehicle 102. In one example, origin 124 can be determined by vehicle 102 using GNSS controller 108. In other examples, vehicle 102 may need to travel to origin 124.

[0054] Destination 126 refers to the final location of route 122. Destination 126 may include an address, latitude and longitude coordinates, intersections, construction site addresses, recently visited locations, meeting locations in the calendar, etc. In some examples, destination 126 can be provided using mobile device 110 before the user enters vehicle 102. For example, destination 126 can be provided to mobile device 110 via user input, and the mobile device is configured to transmit destination 126 to navigation engine 140 when mobile device 110 is in or near vehicle 102. In other examples, destination 126 can be entered into HMI 120 once the user enters vehicle 102. In yet another example, destination 126 can be inferred from information such as the user's calendar and / or various historical route selections for this day of the day or week.

[0055] Route selection preferences 128 include information indicating which factors are important to the occupants when determining the route 122 from origin 124 to destination 126. These route selection preferences 128 may include, for example, a preference for the shortest route 122, a preference for the fastest route 122, and a preference for avoiding highways.

[0056] Weather preference 130 includes information indicating what type of weather conditions 142 the occupants of vehicle 102 prefer. In some cases, weather may not be important to the occupants of vehicle 102. In such cases, weather preference 130 may indicate that weather does not need to be considered when determining route 122. In other cases, weather preference 130 may indicate that the occupants prefer the presence or absence of certain weather conditions 142. For example, occupants hauling cargo in an open trailer may prefer no precipitation, while adventurous occupants may prefer snow. In addition to precipitation, weather preference 130 may also include preferences for other aspects of the weather, such as temperature, wind, or humidity.

[0057] Route selection preference 128 and / or weather preference 130 can vary based on the type of vehicle 102 and / or the task to be performed using vehicle 102. In one example, if vehicle 102 is a convertible, weather preference 130 might prefer sunny or rainless weather events to make driving more enjoyable. In another example, for off-road vehicle 102, weather preference 130 might indicate avoiding weather conditions 142, such as rain or snow, for off-road trail destination 126.

[0058] Navigation application 132 refers to an application executed by mobile device 110 (and in some cases on one or more controllers 104 of vehicle 102) to provide route 122 to vehicle 102. Some exemplary navigation applications 132 include Waze, Apple Maps, and / or Google Maps. To facilitate route selection, in some examples, navigation application 132 communicates via communication network 112 with navigation application server 134 configured to determine route 122.

[0059] Weather application 136 refers to an application executed by mobile device 110 to provide weather condition 142 information to vehicle 102. Some exemplary weather applications 136 include Weather Channel, Underground Weather Station, and AccuWeather. To facilitate the capture of weather conditions 142, weather application 136 may communicate with weather application server 138 via communication network 112.

[0060] Navigation engine 140 refers to the software application executed by controller 104 of vehicle 102 to perform route 122 planning, which is discussed in detail herein. Navigation engine 140 can be configured to receive origin 124, destination 126, route selection preferences 128, and weather preferences 130 transmitted to navigation engine 140 for distribution to one or more mobile devices 110. Navigation engine 140 can then utilize one or more mobile devices 110 to use various navigation application servers 134 to find the route 122 and use a weather application server 138 to find weather conditions 142. This information can be returned to navigation engine 140 for comparison, display to HMI 120, and other processing as discussed herein.

[0061] The navigation engine 140 can be configured to use a data source mapping 144 to determine how to utilize multiple mobile devices 110, navigation application 132, and / or weather application 136 to determine an optimized route 122. In one example, the data source mapping 144 can indicate that one of the mobile devices 110 can be used to simultaneously execute navigation application 132 and / or weather application 136. In another example, the data source mapping 144 can indicate that multiple mobile devices 110 can be connected to the vehicle 102 simultaneously, each mobile device running one or more of the different navigation applications 132 and / or weather applications 136. Vehicle occupants can also stream music from one mobile device 110, stream navigation from another or more mobile devices 110, and stream weather from yet another mobile device 110, allowing different mobile devices 110 to handle these different tasks. This mapping can also be indicated in the data source mapping 144. The data source mapping 144 can be configured by the user using HMI 120.

[0062] Data source mapping 144 can also specify which connectivity interfaces 146 of vehicle 102 should connect to which mobile devices 110. As described herein, the wireless capabilities of vehicle 102's TCU 114, VEC 116, and / or KEC 118 can be used to support connectivity with multiple mobile devices 110. For example, TCU 114 may support connectivity interface 146 for communicating with a single mobile device 110, VEC 116 may support another connectivity interface 146 for communicating with different other mobile devices 110, and KEC 118 may include an antenna array that can provide multiple connectivity interfaces 146 to additional mobile devices 110. In another example, TCU 114 and / or VEC 116 may use vehicle 102's internal modem to support connectivity interfaces 146. By reusing these existing connectivity interfaces 146, vehicle 102 may be able to support connectivity with multiple mobile devices 110 without additional networking hardware. Furthermore, by distributing the operation of various navigation applications 132 and weather applications 136 across multiple devices, system 100 can improve reliability and reduce processing latency.

[0063] Figure 2AAn exemplary navigation application overlay 200 is shown, illustrating multiple routes 122 between origin 124 and destination 126 as determined by a first navigation application 132. The navigation application overlay 200 provides multiple distinct routes 122 (here, routes 122A, 122B, and 122C), each starting from origin 124 and leading to destination 126. Route 122A has a predicted transit time of 24 minutes to destination 126, route 122B has a predicted transit time of 33 minutes to the desired destination 126, and route 122C has a predicted transit time of 33 minutes to destination 126. The first navigation application 132 can also designate one of routes 122A-122C as the recommended route 122 (here, route 122A). These routes 122A-122C can be provided by the first navigation application 132 from a first connected navigation application server 134 and can be transmitted to a navigation engine 140 for processing.

[0064] As shown in the figure, route 122 may include traffic-related route conditions 202. These may include, for example, areas where slowdowns occur due to high traffic volume. These may also include, for example, areas where accidents occur along the road and / or areas where one or more lanes may be congested.

[0065] Navigation engine 140 can be configured to interoperate with multiple navigation applications 132. For example... Figure 2B and Figure 2C As shown, for example, multiple routes 122 can be recommended from an additional navigation application 132 that communicates with the additional navigation application server 134. These different navigation applications 132 can provide similar or identical routes 122 and / or different routes 122. Furthermore, different navigation applications 132 can provide identical or similar routes 122 with different predicted travel times.

[0066] Figure 2B Another navigation application overlay map 200 is shown, featuring three distinct routes 122 (here, routes 122D, 122E, and 122F) extending between origin 124 and destination 126. These routes 122D-122F can be provided from a second-connected navigation application server 134 using a second navigation application 132 and can be transmitted to a navigation engine 140 for processing. Route 122D has a predicted traverse time of 26 minutes, route 122E has a predicted traverse time of 26 minutes, and route 122E has a predicted traverse time of 31 minutes. Additionally, with... Figure 2ACompared to routes 122A, 122B, and 122C, the second navigation application 132 indicates relevant but slightly different traffic-related route conditions 202 along routes 122D, 122E, and 122F. The second navigation application 132 can also indicate one of routes 122D-122F as the recommended route 122 (route 122D in this case).

[0067] Figure 2C Another navigation application overlay map 200 is shown, showing two different routes 122 (here, routes 122G and 122H) extending between origin 124 and destination 126. These routes 122G-122H can be provided from a third-connected navigation application server 134 using a third navigation application 132 and can be transmitted to the navigation engine 140 for processing. Route 122G has a predicted traverse time of 24 minutes, and route 122H has a predicted traverse time of 27 minutes. Additionally, with... Figures 2A to 2B Compared to routes 122A-122F, the third navigation application 132 again indicates relevant but slightly different traffic-related route conditions 202 along routes 122G and 122H. The third navigation application 132 can also indicate one of routes 122G-122H as the recommended route 122 (route 122G in this case).

[0068] Routes 122A-122G transmitted from mobile device 110 to navigation engine 140 can be processed and aggregated by navigation engine 140. Using the varied routes 122A-122G, navigation engine 140 can determine a recommended route 122 to be displayed to vehicle HMI 120 and / or navigated by vehicle 102.

[0069] Figure 2D An example of an HMI 120 displaying a navigation alert for traffic-related route conditions 202 is shown. In addition to aggregating route 122, the navigation engine 140 can also aggregate the reported traffic-related route conditions 202. The navigation engine 140 can then display the aggregated reported traffic-related route conditions 202 on a navigation application overlay map 200.

[0070] In some cases, different navigation applications 132 may report the same or similar traffic-related route conditions 202. To address this, navigation engine 140 can compare any reported traffic-related route conditions 202 displayed for each route 122 provided by each navigation application server 134. To avoid redundancy in aggregation, navigation engine 140 can use AI techniques, such as basic generative machine learning models (e.g., Claude, ChatGPT, llama, etc.), to determine whether the provided routes 122 all include the same or different traffic-related route conditions 202. In one example, navigation engine 140 may provide the model with route 122 and a prompt asking whether the route includes the same or different traffic-related route conditions 202. The model can return a response with an answer. If route 122 is determined to include the same or related traffic-related route conditions 202, those traffic-related route conditions 202 can be combined and displayed as a single incident. Navigation engine 140 can display one or more specific incidents along with the source of the information (or multiple sources in the case of a combination of related incidents).

[0071] like Figure 2D As shown, a single aggregated traffic-related route condition 202 is reported on HMI 120, as if reported by multiple navigation applications 132. Traffic-related route condition 202 states "Report to the police station in advance via the first, second, and third navigation applications." Although not shown, when traffic-related route conditions 202 are different, navigation engine 140 can report specific traffic-related route conditions 202 individually from each source.

[0072] Figure 2E An example of an HMI 120 is shown, displaying multiple images and warnings of traffic-related route conditions 202 from a first navigation application 132, a second navigation application 132, and a third navigation application 132, as well as weather-related route conditions 204 from a weather application 136. As shown, the traffic-related route conditions 202 from the first, second, and third navigation applications 132 are combined into a single report in the HMI 120, stating that "the first navigation application 132 reports advance traffic congestion on the roadside, the second navigation application 132 reports congestion history, and the third navigation application 132 reports railroads." Alternatively, the HMI 120 system may also use voice generation to provide auditory alerts to the user.

[0073] Additionally, weather-related route information 204 received from the weather application 136 is also displayed in the navigation application overlay map 200 to HMI 120. Weather-related route information 204 displays weather condition 142, which is "Winter Weather Report until 1:00 AM Eastern Standard Time on Saturday".

[0074] Figure 3 An exemplary process 300 is shown for providing an optimized navigation route 122 to a destination 126 using a navigation engine 140 that communicates with multiple navigation applications 132 and / or a weather application 136. In one example, process 300 may be performed by a navigation engine 140 that communicates with one or more mobile devices 110. Process 300 may begin when the origin 124 and the destination 126 have been received or otherwise made available to the navigation engine 140.

[0075] At operation 302, navigation engine 140 receives route selection preference 128 and / or weather preference 130 for determining route 122. This includes receiving an indication of whether the weather is important. If the weather is important, navigation engine 140 retrieves weather preference 130 from the storage device of vehicle 102, and / or receives weather preference 130 from HMI 120, and control proceeds to operation 304. Otherwise, control proceeds to operation 308.

[0076] At operation 304, navigation engine 140 utilizes one or more mobile devices 110 to obtain weather conditions 142. In one example, navigation engine 140 communicates with one or more mobile devices 110 to request weather conditions 142 from a weather application 136 executed by the mobile device 110. As a variation, one of the weather applications 136 may be executed by vehicle 102 (e.g., via one or more controllers 104, such as a controller providing connectivity interface 146 or another controller 104). The weather application 136 may then communicate with one or more weather application servers 138 to obtain weather conditions 142 between origin 124 and desired destination 126. In an example where multiple weather forecasts are received, navigation engine 140 may compare the weather conditions 142 between origin 124 and destination 126 to determine if there are any discrepancies in the received weather conditions 142. In a simple example, navigation engine 140 may average the received temperatures. In another example, navigation engine 140 may follow the weather application 136 deemed most reliable. In yet another example, navigation engine 140 can use the worst-case weather conditions reported. This aggregation allows navigation engine 140 to provide weather conditions 142 with a higher degree of accuracy.

[0077] At operation 306, navigation engine 140 optimizes route 122 based on weather conditions 142. In some cases, navigation engine 140 may add waypoints along route 122 to allow navigation application 132 to avoid areas where weather conditions 142 and weather preferences 130 are inconsistent. In other cases, navigation engine 140 may identify areas that route 122 must traverse, and then route 122 should be included in or excluded from the final recommended route. After operation 306, control proceeds to operation 308.

[0078] At operation 308, navigation engine 140 provides origin 124 and destination 126 to multiple navigation applications 132. In one example, navigation engine 140 may utilize one or more mobile devices 110 connected to vehicle 102 to access the multiple navigation applications 132. As a variation, one of the navigation applications 132 may be executed by vehicle 102 (e.g., via one or more controllers 104, such as a controller providing connectivity interface 146 or another controller 104). Each of the multiple navigation applications 132 can then, for example, use their respective navigation application server 134 to obtain multiple routes 122 between origin 124 and the desired destination 126. Examples of such routes 122 are shown in... Figures 2A to 2C As shown in the image.

[0079] At operation 310, navigation engine 140 receives routes 122 from multiple navigation applications 132. Route 122 may include a path from origin 124 to destination 126, and in many cases includes estimated travel time. Additionally, route 122 may include traffic-related route conditions 202 that may affect traffic flow between origin 124 and the desired destination 126, such as the presence of traffic jams, police stations, etc. Navigation application servers 134 may also provide their respective recommended routes 122. In some examples, navigation engine 140 may use route selection preferences 128 (e.g., choosing fastest, shortest, avoiding highways, etc.) to override the determination of recommended routes 122.

[0080] As a variation of operations 306-310, in an alternative example, navigation engine 140 may utilize weather conditions 142 obtained at operation 304 to determine a recommended route 122. For example, navigation engine 140 may filter routes 122 received from navigation application 132 to exclude any routes 122 that do not meet weather preference 130 based on weather conditions 142. Based on the filtered routes 122, navigation engine 140 may similarly identify the most recommended route 122 from the remaining routes 122.

[0081] At operation 312, navigation engine 140 aggregates the received route 122. In one example, navigation engine 140's machine learning optimization algorithm aggregates the recommended route 122 to determine if there are any inconsistencies and calculates the optimal navigation route 122 to travel and reach the desired destination 126.

[0082] At operation 314, navigation engine 140 determines whether route 122 is consistent. In one example, if recommended route 122 is consistent, or if most recommended routes 122 are consistent, navigation engine 140 can select that route as the optimized route 122.

[0083] As a more specific example, route selection preference 128 could indicate that the occupants prefer the fastest route 122. In this case, multiple navigation applications 132 could indicate the same route 122 as the fastest, but the specific time estimates could vary. To determine consistency, the navigation engine 140 could check whether the variation is within a predefined threshold, such as within a predefined number of minutes (e.g., five minutes) or within a predefined percentage of the travel time (e.g., 10%). If so, route 122 can be considered reliable and consistent, and the fastest route 122 can be selected as the optimal route 122. However, if the time variation exceeds the predefined threshold, the time of route 122 can be considered uncertain and less reliable. In yet another possibility, if navigation applications 132 indicate different routes 122 as the fastest, route 122 can also be indicated as uncertain and less reliable.

[0084] Regardless of the method, if route 122 is deemed consistent and / or reliable, control proceeds to operation 316. Otherwise, control proceeds to operation 318.

[0085] At operation 316, navigation engine 140 selects consistent route 122 as the optimal route 122. In one example, route 122 can be displayed to HMI 120. In another example, route 122 can be applied to the autonomous or semi-autonomous functions of vehicle 102 to guide vehicle 102 to destination 126. After operation 318, process 300 ends.

[0086] At operation 318, when navigation application 132 indicates a difference in route 122, the difference can be displayed to HMI 120. Therefore, the occupant may be able to use HMI 120 to understand and resolve the difference. In another example, HMI 120 may provide an option that, when selected, allows the user to choose which route in 122 to follow. In yet another example, HMI 120 may provide the user with the option to intervene by pulling over to view the data. In yet another example, if vehicle 102 is operating in autonomous mode (or can switch to autonomous mode), the occupant can use HMI 120 to view route 122 and choose which different route in 122 to follow.

[0087] In yet another example, HMI 120 can provide a list of navigation applications 132. HMI 120 can allow occupants to define or adjust the priority order of which navigation applications 132 depend on which other navigation applications 132 in the event of inconsistencies in route 122. For example, HMI 120 can allow users to rank navigation applications 132 in descending order of priority.

[0088] In yet another example, navigation engine 140 can allow users to utilize crowdsourced data 502 to verify and / or expand route 122. The following is about... Figure 5 Discuss various aspects of the use of crowdsourced data 502. Regardless of the method used, process 300 ends after operation 318.

[0089] Figure 4 An exemplary process 400 is shown for providing notifications of traffic-related route conditions 202 and / or weather-related route conditions 204 using a navigation engine 140 that communicates with multiple navigation applications 132 and / or weather applications 136.

[0090] At operation 402, navigation engine 140 utilizes one or more mobile devices 110 to receive traffic-related route conditions 202 and / or weather-related route conditions 204. In one example, similar to that discussed with respect to operations 302 and 308-310, navigation engine 140 may utilize one or more mobile devices 110 to access multiple navigation applications 132 and / or weather applications 136. As a variation, one or more of navigation applications 132 and / or weather applications 136 may be executed by vehicle 102 (e.g., via one or more controllers 104, such as a controller providing connectivity interface 146 or another controller 104). These traffic-related route conditions 202 and / or weather-related route conditions 204 may initially be received, for example, along with route 122 and / or weather conditions 142. In another example, after vehicle 102 has begun moving along route 122, traffic-related route conditions 202 and / or weather-related route conditions 204 may be received over time. In either case, navigation engine 140 may receive zero or more traffic-related route conditions 202 from multiple navigation applications 132. Navigation engine 140 may also receive zero or more weather-related route conditions 204 from one or more weather applications 136.

[0091] At operation 404, navigation engine 140 compares traffic-related route conditions 202 and / or weather-related route conditions 204. In one example, navigation engine 140 may provide a machine learning model with route 122 and a prompt asking whether the route conditions include the same or different traffic-related route conditions 202 and / or weather-related route conditions 204. In another example, the prompt may ask whether weather-related route conditions 204 appear to be related to traffic-related route conditions 202. The result can be returned from the model to navigation engine 140.

[0092] At operation 406, navigation engine 140 determines whether redundant issues have been received. For example, if the model indicates route 122 as including the same or related traffic-related route conditions 202 and / or weather-related route conditions 204, control proceeds to operation 408 to combine these issues and display them as a combined traffic-related route condition 202 or weather-related route condition 204. Otherwise, control proceeds to operation 410 to display unrelated traffic-related route conditions 202 and / or weather-related route conditions 204 separately.

[0093] At operation 408, navigation engine 140 displays combined traffic-related route conditions 202 and / or weather-related route conditions 204 to HMI 120. An example of such combined issues is... Figure 2D and Figure 2E As shown in the diagram. After operation 408, control returns to operation 402.

[0094] At operation 410, navigation engine 140 separately displays unrelated traffic-related route conditions 202 and / or weather-related route conditions 204. At operation 410, control returns to operation 402.

[0095] Variations of processes 300 and 400 are possible. In one example, while traversing route 122, navigation application 132 and / or weather application 136 can continuously provide the current position of vehicle 102 (e.g., as determined by GNSS controller 108). Based on the updated position, navigation engine 140 can receive updated route 122 and / or weather conditions 142 from navigation application server 134 and / or weather application server 138. As the vehicle proceeds to destination 126, this information flow can be used to provide updates to route 122 and / or updates to traffic-related route conditions 202 and weather-related route conditions 204.

[0096] Figure 5 An illustrative example 500 is shown in which vehicle 102 utilizes crowdsourced data 502 from crowdsourced data device 504 to verify and / or augment the operation of navigation engine 140. In example 500, vehicle 102 may utilize crowdsourced data 502 collected from one or more other vehicles 102', bystander mobile devices 506, and / or cameras 508. This data can also be used as an additional data source in addition to navigation application 132 and weather application 136.

[0097] Crowdsourced data 502 refers to data captured by crowdsourced data device 504, which can be used to help navigation engine 140 determine route 122. Crowdsourced data 502 may include data such as images, videos, audio, temperature data, humidity data, etc.

[0098] In one example, one or more other vehicles 102' may utilize their sensors 106 to provide crowdsourced data 502 about roads that vehicle 102 may traverse. In another example, one or more bystander mobile devices 506 may be used to capture images, videos, and / or audio that can provide crowdsourced data 502 to vehicle 102. In yet another example, a camera 508, such as a highway traffic camera or a vehicle presence detection camera, may be used as a source of fixed-location crowdsourced data 502. In many examples, it may be necessary for vehicle 102, bystander mobile devices 506, and / or cameras 508 to allow the owner or operator to choose to share the crowdsourced data 502.

[0099] Vehicle 102 and crowdsourcing data device 504 can exchange messages via communication network 112 and / or via V2X communication. For example, vehicle 102 can send a message requesting crowdsourcing data device 504 to provide crowdsourcing data 502 to vehicle 102 within the range between origin 124 and destination 126 and / or along route 122. In one example, this message can be sent as a V2X broadcast, or it can be sent to communication network 112, which can then forward the message to any opt-in crowdsourcing data device 504 connected to the same cell tower as vehicle 102.

[0100] Crowdsourced data 502 can be used to help vehicle 102 select a preferred route 122. This can be useful when there are inconsistencies in routes 122 provided from different navigation applications 132. It can also be useful for areas where the navigation engine 140 has limited access to maps, weather, or traffic information from navigation application server 134 and / or weather application server 138. For example, a camera 508 along the road can visually show rain or snow in areas not covered by weather forecasts.

[0101] The navigation engine 140 can use crowdsourced data 502 as an additional source to update and confirm route 122 and weather conditions 142 as the vehicle 102 travels toward destination 126. Therefore, route 122 can be updated in response to updated route 122 and / or weather conditions 142 provided by navigation application 132, weather application 136, and / or crowdsourced data 502.

[0102] The navigation engine 140 can also be configured to generate and transmit status messages. Status messages can be provided in response to predetermined events, such as changes in arrival time at destination 126 or delays in travel. In one example, status messages can be provided to interested remote devices 510 (such as a family member's handheld device, another vehicle 102', or a field dispatcher). Status messages can be sent via various communication protocols, such as via communication network 112, via V2X, etc., and can be in the form of email, text messages, etc. For example, destination 126 can identify the recipient of the status message by email address or mobile phone number. As a possible use case, a field dispatcher can be notified when a material package arrives at destination 126 and vehicle 102 is available for additional work. Alternatively or additionally, workers or businesses can receive status messages shortly before vehicle 102 arrives at destination 126 as a reminder to be ready to receive the material package. In some possible approaches, vehicle 102 is an autonomous vehicle 102 configured to operate in autonomous (e.g., driverless) mode, partially autonomous mode, and / or non-autonomous mode.

[0103] In another example, navigation engine 140 may use route selection preference 128 and weather preference 130 to perform optimizations to adjust waiting times for a given weather scenario (e.g., waiting in an unshaded area when it is cold and snowy or hot may be less preferable than slowing down in sunny and mild weather).

[0104] As an incentive for the owner and / or operator of the crowdsourced data device 504 to collect crowdsourced data 502, the owner and / or operator of vehicle 102 can utilize navigation engine 140 to provide rewards for surveying route 122 and for collecting real-time information or even alternative route 122 suggestions. These rewards can be combined to incentivize the owner or operator of the crowdsourced data device 504 to travel along the proposed navigation route 122 to capture crowdsourced data 502 in order to receive rewards.

[0105] Figure 6 An exemplary computing device 602 is shown for implementing a navigation system 100 in vehicle 102. (Reference) Figure 6 and refer to Figures 1 to 5 Vehicle 102, controller 104, TCU 114, communication network 112, sensor 106, GNSS controller 108, HMI 120, mobile device 110, navigation application server 134, weather application server 138, and navigation engine 140 are examples of such computing devices 602. Computing device 602 typically includes computer-executable instructions, such as those of navigation engine 140, navigation application server 134, weather application server 138, and process 300, wherein these instructions can be executed by one or more computing devices 602. The computer-executable instructions can be compiled or interpreted according to computer programs created using various programming languages ​​and / or technologies, individually or in combination, including but not limited to Java™, C, C++, C#, Visual Basic, JavaScript, Python, Perl, etc. Generally, a processor (e.g., a microprocessor) receives instructions from sources such as memory, computer-readable media, etc., and executes these instructions to perform one or more processes, including one or more of the processes described herein (e.g., process 300, process 400). Such instructions and other data (such as destination 126, route selection preference 128, weather preference 130) can be stored and transmitted using a variety of computer-readable media.

[0106] As shown in the figure, computing device 602 may include processor 604, which is operatively connected to storage device 606, network device 608, output device 610, and input device 612. It should be noted that this is merely an example, and computing device 602 with more, fewer, or different components may be used.

[0107] Processor 604 may include one or more integrated circuits that implement the functions of a central processing unit (CPU) and / or a graphics processing unit (GPU). In some examples, processor 604 is a system-on-a-chip (SoC) that integrates the functions of both the CPU and GPU. The SoC may optionally include other components, such as storage device 606 and networking device 608, into a single integrated device. In other examples, the CPU and GPU are connected to each other via peripheral connectivity devices, such as peripheral component interconnect (PCI) fast, or another suitable peripheral data connection. In one example, the CPU is a commercially available central processing unit that implements an instruction set, such as x86, ARM, Power, or a family of microprocessor instruction sets without interlocked pipeline stages (MIPS).

[0108] Regardless of the details, during operation, processor 604 executes stored program instructions retrieved from storage device 606. The stored program instructions accordingly include software that controls the operation of processor 604 to perform the operations described herein. Storage device 606 may include both non-volatile memory and volatile memory devices. Non-volatile memory includes solid-state memory, such as NAND flash memory, magnetic and optical storage media, or any other suitable data storage device that retains data when the system is disabled or loses power. Volatile memory includes static and dynamic random access memory (RAM) that stores program instructions and data during operation of the optimized route navigation system 100.

[0109] The GPU may include hardware and software for displaying at least two-dimensional (2D) and optionally three-dimensional (3D) graphics to the output device 610. The output device 610 may include a graphics or visual display device, such as an electronic display screen, projector, printer, or any other suitable device for reproducing a graphic display. As another example, the output device 610 may include an audio device, such as a speaker or headphones. As yet another example, the output device 610 may include a tactile device, such as a mechanically elevable device, which in one example may be configured to display Braille or be another physical output that can be touched to provide information to an occupant.

[0110] Input device 612 may include any of a variety of devices that enable computing device 602 to receive control input from an occupant. Examples of suitable input devices 612 for receiving human-machine interface input may include a keyboard, mouse, trackball, touchscreen, microphone, graphics tablet, etc.

[0111] Network device 608 may each include any of a variety of means that enable the described components to send and / or receive data over a network and from external devices. Examples of suitable network devices 608 include an Ethernet interface, a Wi-Fi transceiver, a cellular transceiver, or a Bluetooth or BLE transceiver, or other network adapters or peripheral interconnects that may be useful for efficiently receiving large datasets.

[0112] Regarding the processes, systems, methods, heuristics, etc., described herein, it should be understood that although the steps of such processes, etc., have been described as occurring in a certain ordered order, such processes can be practiced with the described steps performed in a different order than that described herein. It should also be understood that some steps may be performed simultaneously, other steps may be added, or some steps described herein may be omitted. In other words, the description of processes herein is provided for the purpose of illustrating certain embodiments and should in no way be construed as limiting the claims.

[0113] Therefore, it should be understood that the above description is intended to be illustrative rather than restrictive. Many embodiments and applications beyond the examples provided will become apparent upon reading the above description. The scope should not be determined by reference to the above description, but rather by reference to the appended claims and the full scope of their equivalents. It is anticipated and expected that the techniques discussed herein will evolve in the future, and the disclosed systems and methods will be incorporated into such future embodiments. In conclusion, it should be understood that modifications and variations are possible with this application.

[0114] All terms used in the claims are intended to give their broadest reasonable structure and their general meaning as would be understood by one of skill in the art described herein, unless explicitly indicated otherwise herein. Specifically, unless the claims explicitly limit the recitation to the contrary, the use of singular articles such as “a,” “the,” or “the” should be interpreted as one or more of the elements indicated by the recitation.

[0115] An abstract of this disclosure is provided to allow the reader to quickly determine the nature of this technical disclosure. It should be understood that the abstract is not intended to interpret or limit the scope or meaning of the claims. Furthermore, as can be seen in the foregoing detailed description, various features are grouped together in various embodiments for the purpose of making the disclosure fluent. This approach of the disclosure should not be construed as reflecting an intention to require more features than expressly stated in each claim. Rather, as reflected in the appended claims, the inventive subject matter lies in fewer than all features of a single disclosed embodiment. Therefore, the appended claims are hereby incorporated into the detailed description, wherein each claim is itself a separately claimed subject matter.

[0116] Although exemplary embodiments have been described above, these embodiments are not intended to describe all possible forms of this disclosure. Rather, the terminology used herein is descriptive rather than restrictive, and it should be understood that various changes may be made without departing from the spirit and scope of this disclosure. Furthermore, features of various embodiments may be combined to form other embodiments of this disclosure.

[0117] According to the present invention, a vehicle for determining an optimal route is provided, comprising: one or more controllers providing at least one connectivity interface configured to connect to a plurality of navigation applications executed by the one or more controllers and / or by one or more mobile devices; and a navigation engine executed by at least one of the one or more controllers, the navigation engine being configured to: receive multiple routes from origin to destination from each of the plurality of navigation applications, including identifying recommended routes from each of the plurality of navigation applications to define a set of recommended routes, aggregating the recommended routes to determine differences between the recommended routes, utilizing the recommended routes as optimized routes for the vehicle in response to consistency of the recommended routes, and displaying the differences in the vehicle's human-machine interface (HMI) in response to inconsistency of the recommended routes.

[0118] According to an embodiment, the at least one connectivity interface includes a plurality of connectivity interfaces, and the one or more controllers providing the plurality of connectivity interfaces include at least two of a telematics control unit (TCU), a vehicle entertainment controller, and a keyless entry controller.

[0119] According to an embodiment: the first navigation application in the plurality of navigation applications is executed by the first mobile device in the one or more mobile devices, and the second navigation application in the plurality of navigation applications is executed by the second mobile device in the one or more mobile devices.

[0120] According to an embodiment, the plurality of navigation applications include a plurality of navigation applications executed by one of the one or more mobile devices.

[0121] According to an embodiment: the first navigation application among the plurality of navigation applications is executed by the one or more controllers, and the second navigation application among the plurality of navigation applications is executed by the first mobile device among the one or more mobile devices.

[0122] According to an embodiment, the navigation engine is further configured to: use one or more weather applications executed by the one or more mobile devices to retrieve weather conditions associated with the multiple routes; and optimize the recommended routes based on user-defined weather preferences and the retrieved weather conditions.

[0123] According to an embodiment, in response to all routes in the recommended routes changing within a predefined time threshold, the navigation engine determines the recommended routes to be consistent.

[0124] According to an embodiment, in response to the fact that most of the recommended routes are consistent, the navigation engine determines that the recommended routes are consistent.

[0125] According to an embodiment, the navigation engine is further configured to: receive a first traffic-related route condition from a first navigation application among the plurality of navigation applications; receive a second traffic-related route condition from a second navigation application among the plurality of navigation applications; utilize a machine learning model to determine whether the first traffic-related route condition and the second traffic-related route condition confirm a problem along the optimized route; in response to the first traffic-related route condition and the second traffic-related route condition indicating a confirmed problem, display the confirmed problem in the HMI as identified by the first navigation application and the second navigation application; and otherwise, display the first traffic-related route condition and the second traffic-related route condition as separate problems in the HMI.

[0126] According to an embodiment, the navigation engine is further configured to: send a message to a crowdsourcing data monitoring device to request crowdsourcing data; and receive the crowdsourcing data from the crowdsourcing data device to verify and / or supplement the traffic-related route conditions from the navigation application.

[0127] According to the present invention, a method for determining an optimal route for a vehicle includes: receiving multiple routes from a point of origin to a destination from each of a plurality of navigation applications executed by one or more controllers and / or by one or more mobile devices communicating with the vehicle via at least one connectivity interface; identifying recommended routes from each of the plurality of navigation applications to define a set of recommended routes; aggregating the recommended routes to determine differences between the recommended routes; utilizing the recommended routes as the optimized route for the vehicle in response to consistency among the recommended routes; and displaying the differences in the vehicle's HMI in response to inconsistency among the recommended routes.

[0128] In one aspect of the invention, the method includes providing a plurality of connectivity interfaces using at least two of the vehicle's TCU, the vehicle's infotainment controller, and the vehicle's keyless entry controller, wherein a first navigation application among the plurality of navigation applications is executed by a first mobile device among the one or more mobile devices, and wherein a second navigation application among the plurality of navigation applications is executed by a second mobile device among the one or more mobile devices.

[0129] In one aspect of the invention, the method includes: using one or more weather applications executed by the one or more mobile devices to retrieve weather conditions associated with the plurality of routes; and optimizing the recommended routes based on user-defined weather preferences and the retrieved weather conditions.

[0130] In one aspect of the invention, the method includes one of the following: determining the recommended routes as consistent in response to all routes in the recommended routes changing within a predefined time threshold; or determining the recommended routes as consistent in response to most routes in the recommended routes being consistent.

[0131] In one aspect of the invention, the method includes: receiving first traffic-related route information from a first navigation application among the plurality of navigation applications; receiving second traffic-related route information from a second navigation application among the plurality of navigation applications; using a machine learning model to determine whether the first traffic-related route information and the second traffic-related route information confirm a problem along the optimized route; in response to the first traffic-related route information and the second traffic-related route information indicating a confirmed problem, displaying the confirmed problem in the HMI as identified by the first navigation application and the second navigation application; and otherwise, displaying the first traffic-related route information and the second traffic-related route information as separate problems in the HMI.

[0132] In one aspect of the invention, the method includes: sending a message to a crowdsourcing data monitoring device to request crowdsourcing data; and receiving the crowdsourcing data from the crowdsourcing data device to verify and / or supplement the traffic-related route conditions from the navigation application.

[0133] According to the present invention, a non-transitory computer-readable medium is provided having instructions for determining an optimal route for a vehicle, the instructions, when executed by one or more controllers of the vehicle, causing the vehicle to perform operations including: providing a plurality of connectivity interfaces using at least two of the vehicle's TCU, the vehicle's infotainment controller, and the vehicle's keyless entry controller; receiving multiple routes from origin to destination from each of a plurality of navigation applications executed by the one or more controllers and / or by a plurality of mobile devices communicating with the vehicle through the plurality of connectivity interfaces; identifying recommended routes from each of the plurality of navigation applications to define a set of recommended routes; aggregating the recommended routes to determine differences between the recommended routes; utilizing the recommended routes as the optimized route for the vehicle in response to agreement between the recommended routes; and displaying the differences in the vehicle's HMI in response to disagreement between the recommended routes.

[0134] According to an embodiment, the invention is further characterized in that, when executed by one or more controllers of the vehicle, it causes the vehicle to perform operations including: using one or more weather applications executed by the plurality of mobile devices to retrieve weather conditions associated with the plurality of routes; and optimizing the recommended routes based on user-defined weather preferences and the retrieved weather conditions.

[0135] According to an embodiment, the invention is further characterized in that, when executed by one or more controllers of the vehicle, the vehicle performs an instruction comprising the operation of determining the recommended route as consistent in response to at least a majority consistency of the recommended route.

[0136] According to an embodiment, the invention is further characterized in that, when executed by one or more controllers of the vehicle, it causes the vehicle to perform an instruction comprising the following operations: receiving a first traffic-related route condition from a first navigation application among the plurality of navigation applications; receiving a second traffic-related route condition from a second navigation application among the plurality of navigation applications; using a machine learning model to determine whether the first and second traffic-related route conditions confirm a problem along the optimized route; in response to the first and second traffic-related route conditions indicating a confirmed problem, displaying the confirmed problem in the HMI as identified by the first and second navigation applications; and otherwise, displaying the first and second traffic-related route conditions as separate problems in the HMI.

[0137] According to an embodiment, the invention is further characterized in that, when executed by one or more controllers of the vehicle, it causes the vehicle to perform operations including: sending a message to a crowdsourcing data monitoring device to request crowdsourcing data; and receiving the crowdsourcing data from the crowdsourcing data device to verify and / or supplement the traffic-related route conditions from the navigation application.

Claims

1. A vehicle for determining an optimal route, comprising: One or more controllers, the one or more controllers providing at least one connectivity interface configured to connect to multiple navigation applications executed by the one or more controllers and / or by one or more mobile devices; and A navigation engine, executed by at least one of the one or more controllers, is configured to: Receive multiple routes from origin to destination from each of the plurality of navigation applications, including identifying recommended routes from each of the plurality of navigation applications to define a set of recommended routes. The recommended routes are aggregated to determine the differences between them. In response to the recommended route, the recommended route is used as the optimized route for the vehicle, and In response to the inconsistency in the recommended routes, the difference is displayed in the vehicle's human-machine interface (HMI).

2. The vehicle of claim 1, wherein the at least one connectivity interface comprises a plurality of connectivity interfaces, and the one or more controllers providing the plurality of connectivity interfaces comprise at least two of a telematics control unit (TCU), a vehicle entertainment controller, and a keyless entry controller.

3. The vehicle as claimed in claim 1, wherein: The first navigation application among the plurality of navigation applications is executed by the first mobile device among the one or more mobile devices, and The second navigation application among the multiple navigation applications is executed by the second mobile device among the one or more mobile devices.

4. The vehicle of claim 1, wherein the plurality of navigation applications includes a plurality of navigation applications executed by one of the one or more mobile devices.

5. The vehicle as claimed in claim 1, wherein: The first navigation application among the plurality of navigation applications is executed by the one or more controllers, and The second navigation application among the plurality of navigation applications is executed by the first mobile device among the one or more mobile devices.

6. The vehicle of claim 1, wherein the navigation engine is further configured to: Use one or more weather applications executed by the one or more mobile devices to retrieve weather conditions associated with the multiple routes; and The recommended route is optimized based on user-defined weather preferences and retrieved weather conditions.

7. The vehicle of claim 1, wherein in response to all routes in the recommended route changing within a predefined time threshold, the navigation engine determines the recommended routes to be consistent.

8. The vehicle of claim 1, wherein the navigation engine determines the recommended route as consistent in response to the majority of the recommended routes being consistent.

9. The vehicle of claim 1, wherein the navigation engine is further configured to: Receive first traffic-related route information from the first navigation application among the plurality of navigation applications; Receive second traffic-related route information from the second navigation application among the plurality of navigation applications; A machine learning model is used to determine whether the first and second traffic-related route conditions confirm the problem along the optimized route. In response to a problem confirmed by the first traffic-related route condition and the second traffic-related route condition indication, the confirmed problem is displayed in the HMI as being identified by the first navigation application and the second navigation application; and Otherwise, the first traffic-related route condition and the second traffic-related route condition are presented as separate issues in the HMI.

10. The vehicle of claim 9, wherein the navigation engine is further configured to: Send a message to the crowdsourced data monitoring device to request crowdsourced data; and The crowdsourced data is received from the crowdsourced data device to verify and / or supplement the traffic-related route conditions from the navigation application.

11. A method for determining the optimal route for a vehicle, comprising: Receive multiple routes from origin to destination from each of a plurality of navigation applications executed by the one or more controllers and / or by one or more mobile devices communicating with the vehicle via at least one connectivity interface; Identify recommended routes from each of the plurality of navigation applications to define a set of recommended routes; Aggregate the recommended routes to determine the differences between them; In response to the recommended route, the recommended route is used as the optimized route for the vehicle; and In response to the inconsistency in the recommended routes, the difference is displayed in the vehicle's HMI.

12. The method of claim 11, further comprising: Multiple connectivity interfaces are provided using at least two of the vehicle's TCU, the vehicle's infotainment controller, and the vehicle's keyless entry controller. The first navigation application among the plurality of navigation applications is executed by the first mobile device among the one or more mobile devices, and The second navigation application in the plurality of navigation applications is executed by the second mobile device in the one or more mobile devices.

13. The method of claim 11, further comprising: Use one or more weather applications executed by the one or more mobile devices to retrieve weather conditions associated with the multiple routes; as well as The recommended route is optimized based on user-defined weather preferences and retrieved weather conditions.

14. The method of claim 11, further comprising one of the following: In response to all routes in the recommended routes changing within a predefined time threshold, the recommended routes are determined to be consistent; or If the majority of the recommended routes are consistent, the recommended routes are determined to be consistent.

15. The method of claim 11, further comprising: Receive first traffic-related route information from the first navigation application among the plurality of navigation applications; Receive second traffic-related route information from the second navigation application among the plurality of navigation applications; A machine learning model is used to determine whether the first and second traffic-related route conditions confirm the problem along the optimized route. In response to a problem confirmed by the first traffic-related route condition and the second traffic-related route condition indication, the confirmed problem is displayed in the HMI as being identified by the first navigation application and the second navigation application; Otherwise, the first traffic-related route condition and the second traffic-related route condition are presented as separate issues in the HMI; and Optionally, a message may be sent to a crowdsourced data monitoring device to request crowdsourced data, and the crowdsourced data may be received from the crowdsourced data device to verify and / or supplement the traffic-related route conditions from the navigation application.

Images