Terrain-based vehicle navigation and control

Abstract

Various systems and methods are disclosed for providing a wide range of tools for selecting routes based on road, vehicle, and vehicle occupant information. Also disclosed are the costs and trade-offs that may be associated with various choices, including wear on vehicle components, occupant discomfort, increased trip duration, and efficiency loss.

Description

TECHNICAL FIELD

[0001] Related Application This application claims the benefit of U.S. Provisional Patent Application No. 63 / 014,210, filed on April 23, 2020, under 35 U.S.C. § 119(e). The disclosure of the aforementioned application is incorporated herein by reference in its entirety.

[0002] Field The disclosed embodiments relate to vehicle control and route selection based at least in part on road surface information, vehicle information, and vehicle occupant information collected while traversing a road surface. BACKGROUND ART

[0003] Background GNSS-based navigation systems in use today may be capable of recommending one or more routes to reach a destination. Such systems may indicate the fastest route to travel to the destination, allow a driver to select a desired route, and guide the driver on what roads to take to reach the desired destination. SUMMARY OF THE INVENTION MEANS FOR SOLVING THE PROBLEMS

[0004] Summary Various systems and methods are disclosed for providing a wide range of tools for selecting a route based on road information, vehicle information, and vehicle occupant information.

[0005] A method for operating a vehicle is provided, comprising: receiving information about two or more routes between a first place and a second place; receiving vehicle-specific information about the vehicle; selecting a route from the two or more routes based at least in part on the received information; and driving the vehicle along the selected route by driving or operating autonomously. In some embodiments, parts of the two or more routes may overlap at least partially with each other. In some embodiments, parts of the received information may include information about the road surface of at least part of the two or more routes. In some embodiments, the received information may include data from a GNSS (e.g., GPS) and / or terrain-based location system regarding the location of the vehicle. In some embodiments, the first place may be the vehicle's current location, and the second place may be the vehicle's destination. In some embodiments, the vehicle may be an autonomous vehicle, a semi-autonomous vehicle, and a manually driven vehicle. The received information may include information about the transfer function of the vehicle's suspension system or its output. In some embodiments, the vehicle's suspension system may be an active suspension system. In some embodiments, the received information may include information about the location of the vehicle's center of gravity. Depending on the embodiment, the received information may include information regarding the estimated speed of the vehicle. Depending on the embodiment, the received information may include information regarding the estimated or expected speed of the vehicle when traveling along at least part of two or more routes. Depending on the embodiment, the method may include determining estimated road-induced disturbances when traveling along two or more routes, at least in part, based on the received road surface information and the estimated speed of the vehicle on at least part of those routes, and then selecting or recommending a route, at least in part, based on the information regarding the induced disturbances.Depending on the embodiment, the information received regarding the vehicle may include the vehicle's weight, information about the vehicle occupants (e.g., information about the susceptibility of at least one vehicle occupant to motion sickness, information about the susceptibility of at least one vehicle occupant to motion sickness while performing activities (e.g., reading, operating a computer mouse, etc.), and / or information about estimated activities by at least one vehicle occupant). Depending on the embodiment, a speed range for a selected route is determined at least in part based on the information received regarding the road, the vehicle, and / or the vehicle occupants. The vehicle is then operated within the determined speed range on at least part of the selected route.

[0006] A part of the present disclosure provides a method for operating a vehicle, comprising: receiving information about at least two routes between a first place and a second place; receiving information from a user interface; selecting a route from the at least two routes, wherein the selection is based at least in part on the routes and on information received via the user interface; and having the vehicle (e.g., manually driven or autonomous vehicle) drive along the selected route. In some embodiments, the user interface may be mounted and positioned in the vehicle. In some embodiments, the information received from the user interface may include instructions that reducing tire wear is a preference or priority, reducing motion sickness in vehicle occupants is a preference or priority, reducing lateral acceleration of the vehicle is a preference or priority, and / or reducing vertical acceleration of the vehicle is a preference or priority. In some embodiments, the method may include selecting a speed for at least a portion of the selected route, based at least in part on the road and on information received from the user interface. Depending on the embodiment, the method may include selecting a maximum speed for at least a portion of a selected route, based at least partially on information received from the user interface regarding the road. Depending on the embodiment, the method may include selecting or determining a minimum speed while traveling along at least a portion of the selected route, based at least partially on information received from the user interface regarding the road. Depending on the embodiment, the method may include selecting a lane within the multi-lane portion of the selected route. Depending on the embodiment, the information received regarding the road may include road surface information. Depending on the embodiment, the information received regarding the road may include crowdsourced information.

[0007] A part of the present disclosure provides a method for operating a vehicle, which includes receiving information about at least two routes between the current location and a destination; receiving vehicle-specific information relating to the vehicle; selecting a route from the at least two routes based on the routes and vehicle information to achieve less wear and tear on components, less motion sickness, shorter travel time, and / or higher energy efficiency; and driving along the selected route.

[0008] It should be understood that the concepts described above, and the further concepts described below, may be formed in any suitable combination, as this disclosure is not limited in this respect. Furthermore, other advantages and novel features of this disclosure will become apparent from the following detailed description of various non-limiting embodiments, when considered in relation to the attached drawings. [Brief explanation of the drawing]

[0009] Brief explanation of the drawing [Figure 1] Figure 1 is a schematic diagram of one embodiment of a vehicle controller system. [Modes for carrying out the invention]

[0010] Detailed explanation The inventors recognized that a vehicle-mounted navigation system and / or one or more microprocessor-based controllers may be used to provide users with data in addition to location data. Such additional data may include, for example, travel time, tolls, and other factors. This additional data may be provided to operators (e.g., vehicle drivers, vehicle occupants, and / or autonomous vehicle controllers) in combination with road surface data. This additional data may include, for example, road components, road features, and various other road characteristics. The inventors further recognized that one or more microprocessor-based controllers mounted in a vehicle may receive data from an in-vehicle or remote database, which may include, for example, the following: (i) Vehicle-specific location data that can be derived from terrain-based information and / or GNSS (Global Navigation Satellite System) (i.e., data relating to or indicating the location of the vehicle), (ii) Vehicle-specific information relating to the condition of the vehicle, including, for example, vehicle mass or weight, vehicle suspension transfer function, location of the center of gravity, type / type of various components such as tires, dampers, bushings, and / or degree of wear of various components, (iii) For example, vehicle-specific information relating to one or more vehicle occupants, such as occupant preferences, age, fatigue level, driving skill level, and / or susceptibility to motion sickness. (iv) Vehicle-specific information regarding activities that may be carried out by one or more vehicle occupants, (v) Road-specific information relating to the vehicle's choice of roads, including information relating to road surface abnormalities or defects (e.g., potholes, bumps, cracks, drainage grates, expansion joints) and / or information relating to snow and / or ice on the road surface. (vi) Road-specific road geometry information such as road curvature, road slope, elevation, and / or curvature, (vii) Road-specific information relating to risk factors, such as the likelihood of rock landslides, floods, or accidents, which may be a function of time, weather conditions, visibility, or season, and / or (viii) Meteorological data that may include estimated or measured local temperature and / or precipitation data.

[0011] Depending on the embodiment, one or more controllers, which may include one or more microprocessors, may be used to provide information or recommendations that can assist the driver and / or vehicle controller, based on some or all of such data. Such information may include, for example, recommended roads, routes and / or lane selections and / or driving speeds. Such information may be used by one or more controllers to operate one or more vehicle systems, such as advanced driver assistance systems, active or semi-active suspension, braking, propulsion and / or steering systems.

[0012] Figure 1 shows a vehicle control system 100 that includes a microprocessor-based controller 102 which can be used to provide information or recommendations to the driver via an Advanced Driver-Assistance System (ADAS) 104, or to various other vehicle systems 106, such as an autonomous vehicle controller, an active or semi-active suspension system, a braking system, a stability control system, and / or a steering system. The information and recommendations provided by the controller 102 may be based on information from various on-board or remote sources, such as a road-specific data source 108 that may provide information including risk factor information such as road surface data and / or accident statistics; a meteorological data source 110 that may include local temperature, precipitation, and / or visibility data; and a vehicle-specific data source 112 that may include information about the vehicle, such as the manufacturer, model, and operating characteristics of various systems (e.g., transfer function, vehicle load, center of gravity, vehicle dynamics, current state of various systems (e.g., tire and / or damper wear)); and / or information about one or more vehicle occupants (e.g., susceptibility to motion sickness, driving skills, and / or type of activity). These data sources may receive information from on-board or remote databases (e.g., cloud-based) and / or sensors 114-121. Such sensors may be mounted on a vehicle, mounted on another vehicle, or be part of the infrastructure.

[0013] Depending on the embodiment, a crowdsourced road topographic mapping system may be used to create a high-definition (HD) map that may include road outline, road curvature, road type, and road event information, in addition to other information such as travel time and tolls. The system may acquire road information from connected vehicles using a sensor set that includes sensors or sensor systems, such as GPS, vehicle speed sensors, accelerometers, and / or various other vehicle-based sensors that may differ from vehicle to vehicle. Depending on the embodiment, the system may calculate topographic information such as road outline frequency components, road curvature, road characteristics, and road events such as potholes, speed bumps, cracks, uplifts, and other road surface features, anomalies, or abnormalities, as well as in-plane road curvature (for example, around the vehicle's vertical axis, corresponding to the yaw direction). Depending on the embodiment, correlating information from various vehicles may be used to create an HD map that includes this additional information, such as map metadata for one or more road sections.

[0014] Depending on the embodiment, information regarding road components, road quality, and / or conditions may be derived from HD maps and / or from other relevant or unrelated sources such as weather information, local government information, web resources, user reports, other vehicles (V2V), and / or user feedback.

[0015] In some embodiments, such additional information may be used to provide additional input to the navigation system and / or other in-vehicle systems, for example, to improve route and / or speed selection. As a result, this optimization may be based on variables including travel time, but may also be based on a wider range of variables depending on the use case, which may be relevant to a particular user. In some embodiments, by using such additional information in combination with other parameters, it may be possible to create route navigation that is customized to the end user, for example, the end user vehicle and / or the occupants or driver of the end user vehicle. Multiple factors related to road components may be used and, in some embodiments, may be combined to provide individualized and / or customized route guidance or to provide additional information to the end user.

[0016] For example, road components can affect a vehicle in a manner proportional to its speed, in terms of spatial frequency components. For instance, a 10m long wave on the road surface can create a 1Hz input or disturbance when the vehicle is traveling at 10m / s, but a 3Hz input when the vehicle is traveling at 30m / s. At low speeds, this particular wave may excite vehicle-specific frequencies, such as in the range of 1.0-1.5Hz, and therefore may be perceived as a large input. On the other hand, at higher speeds, such as on a main road, the same wave may excite intermediate frequencies, such as in the range of 1.5Hz-5Hz or higher. At such higher frequencies, some vehicles may more effectively isolate from the input or disturbance, and therefore the road input may be perceived or felt by the vehicle occupants as a smaller or less influential disturbance.

[0017] Depending on the embodiment, a vehicle or various vehicle systems may have a response to a particular road input that can be specified, measured, or estimated, and which can vary with time, environment, parameter settings, and environmental factors such as temperature, humidity, or atmospheric pressure. Examples of such systems include components of a suspension system, such as dampers and / or bushings, which may behave differently depending on temperature or age; tires, which behave differently depending on wear, temperature, humidity, and the presence of snow, ice, or rain; other systems such as engine mount bushings; or systems such as engine exhaust or catalytic converter systems. Knowledge of such a response, which may be called a vehicle transfer function or approximate transfer function, can be used to estimate how a given road input will affect the vehicle and its occupants in terms of comfort, and / or its impact on vehicle handling, comfort, durability, and / or the durability of one or more components of the vehicle.

[0018] In some embodiments, a linear transfer function may be obtained based on the linear response of the system and used to estimate the system's response to a given input or set of inputs while ignoring nonlinear effects. A linear transfer function may be used to estimate the operation of a nonlinear system by linearizing the response around the operating point. Multiple linear responses may be used at multiple operating points to estimate a wide range of responses where the response is nonlinear overall. For example, inputs at or near the vehicle's body resonant frequency (e.g., in some vehicles, in the range of 1.0 Hz to 1.5 Hz for the front or rear axle, a frequency of 1.2 Hz for the front axle, a frequency of 1.4 Hz for the rear axle, a frequency in the range of 2 Hz to 3 Hz in the roll direction, or a frequency of 2.5 Hz in the roll direction) can cause the vehicle to exceed its suspension travel due to suspension displacement caused by road disturbances, and thus can degrade suspension components, for example, by engaging with suspension bumps or rebound stoppers, or by overloading the tires between events. However, the disclosure is not limited in this way, and both body resonant frequencies above and below the ranges indicated above are intended.

[0019] Depending on the embodiment, the response or transfer function may differ for different input directions. For example, in the roll direction (which may be excited by different road components on the left and right sides of the vehicle), the torsion direction (which may be excited when at least a portion of the road input follows a pattern in which the road under one front wheel and the diagonally opposite rear wheel moves in the same direction, while the other two tires move in opposite directions with a phase difference), the heave direction (which may be excited when at least a portion of the road input is applied equally to all four wheels), and the pitch direction (which may be excited by a road component that causes the front wheel to move at least partially in the opposite direction to the rear wheel), or in any combination of these directions. The directivity of the transfer function can be described for various combinations, and the description herein is not limited to those combinations. It is understood that this disclosure is not so limited, and other directions and combinations of directions may also be defined.

[0020] In some embodiments, the road contour information can be used, for example, to estimate wear on one or more sets of vehicle components such as tires, suspension dampers, or steering systems. Rough roads can increase wear on vehicle components, lead to higher repair costs over the service life of the vehicle, and also increase the possibility of catastrophic failure. For example, roads with various surface irregularities or abnormalities such as potholes or speed bumps can also contribute to such degradation. Such degradation can, for example, be determined and / or predicted based on historical data for a given vehicle type, or can be provided as guidance by the vehicle manufacturer. In some embodiments, for example, a tire manufacturer can certify a tire for a specific number of road miles on good quality roads identified as having an international roughness index (IRI) of 1.5 m / km or less, or for a lower number of rough road miles identified as having an IRI of 2.5 m / km or more. Other road roughness or road quality indexes and ranges, both above and below those described above, are contemplated as the present disclosure is not so limited.

[0021] In some embodiments, damper life can be determined or calculated by performing endurance tests in a laboratory. For example, sample dampers can be exposed to a predetermined test sequence or multiple sequences that may include high-speed events, for example, in the range of 2 to 3 m / s. However, speed ranges both above and below 2 to 3 m / s are contemplated as the present disclosure is not so limited. The number of events that a damper model can experience before failure can be used to estimate its service life. In some embodiments, such information can be used to determine or predict the degree of degradation of dampers of the same model when a vehicle equipped with such dampers is operated over a specific route.

[0022] In some embodiments, the navigation system may accumulate the number of miles of good, medium, and rough roads to be traversed, and scale them with respect to tire life, or damper life, or the life of another component. In some embodiments, a user selection setting may determine the importance of the life of one or more components, for example, tire life, for a given user. In some embodiments, the setting may determine a level of importance associated with a component, for example, a tire, based on the estimated remaining useful life of such component. For example, a tire manufacturing company may specify the useful life of a tire as 50,000 miles on good quality roads, or 40,000 miles on medium quality roads, or 20,000 miles on low quality roads, based on an appropriate strategy for grading roads as low, medium, and good quality, for example, based on the relevant IRI of the road. For example, if a tire has been driven for 10,000 miles on low quality roads and 20,000 miles on good quality roads, then the estimated remaining useful life may be 10% (determined using the formula (100-100*(10,000 / 20,000+20,000 / 50,000)) and comparing it to 100%). In some embodiments, for example, the system, a remote or on-board microprocessor-based controller, may automatically select or recommend a longer but higher quality route to save tire life, or alternatively, a shorter but lower quality road to save time.

[0023] Additionally or alternatively, in some embodiments, wear models of other components, for example, such as suspension or chassis components, may be used to predict component life as a function of road parameters. In some embodiments, the expected life model may be, for example, a function of road components within a given frequency range. It is noted that road components may be defined as a function of distance traveled, and the conversion to frequency (that is, as a function of time) may be a function of actual or expected travel speed.

[0024] In some embodiments, the wear model may be a function of events such as pothole collisions. In some embodiments, the wear model of a component (or vehicle) may include sensitivity to specific parameters, such as the size of the pothole encountered and the vehicle's speed at the time of the encounter. Such a wear model may be used to estimate the total damage to a given component based on the number of events of a given type encountered and / or the speed at which the encounter occurred. Each event encounter may be assigned a severity score based on parameters associated with the event and vehicle speed in the HD map, and / or based on acceleration or force measurements, for example, using vehicle-based sensors. In some embodiments, estimating damage to one or more components by passing through a given road section may be used to provide more informed navigation guidance. For example, a navigation route that may encounter several large, and / or unavoidable potholes may result in a longer travel time, but may be less desirable than a navigation route that minimizes encounters with harmful road events, such as potholes. In some embodiments, a component damage or failure model may be used to predict the probability of a catastrophic failure. Damage or failure models may be based, for example, on determining and tracking the actual stresses or strains to which the components are exposed, experimental simulations relating wear or damage to exposure to various stresses (which may include, for example, crowdsourced wear data for the same or similar components in the same or similar type of vehicle), and / or manufacturer recommendations or specifications.

[0025] In some embodiments, for example, a comfort model may be used to consider the level of discomfort induced by road inputs. In some embodiments, road inputs that may be considered may include, for example, the interaction with potholes, speed bumps, and / or road undulations as a function of predicted driving speed. Such factors can significantly reduce occupant comfort or perceived comfort. In some embodiments, information on vehicle type and driving speed may be considered, along with road inputs, to create an overall comfort or discomfort metric. In some embodiments, the user may prefer to select the road and speed that best suits their current condition and / or their desired level of comfort.

[0026] Depending on the embodiment, another factor that may be considered is fuel or electrical energy consumption. Different road types, and in particular different road profiles, can result in different fuel or energy consumption. Depending on the embodiment, a navigation or vehicle control system may use road profile information to refine expected fuel consumption and use that information when providing optimal route guidance.

[0027] In some embodiments, motion sickness may be considered when selecting or recommending a route. The likelihood or expected severity of motion sickness on a particular road at expected or planned speeds may be used to refine the route selection or recommendation process. In some embodiments, this process may take into account the susceptibility of one or more occupants of the vehicle. In some embodiments, the consideration or weight given to motion sickness for route selection or recommendation may depend, in addition to road type or profile, on occupant identification, information on their susceptibility to motion sickness, and / or activities they are doing or may be doing. In some embodiments, the motion sickness model may be based on empirical data collected on similar roads for a given vehicle occupant, and expected speed. If the vehicle occupants are known not to be highly susceptible and / or do not intend to or do not engage in activities such as reading, then motion sickness may not be considered, or may be given little or no weight. However, if one or more occupants are highly susceptible to motion sickness, motion sickness may be given additional weight.

[0028] In some embodiments, this information regarding susceptibility to motion sickness may be used, for example, along with information about current traffic conditions and likely crossing speeds, to assign a relative motion sickness score to each section of a proposed route. Such information may be used to optimize a route for a combination or subset of factors such as travel time, fuel consumption, and other factors, such as the tendency of a proposed route to induce motion sickness, assuming the susceptibility of one or more occupants. In some embodiments, if the driver of the vehicle is the sole occupant, this component of optimal route selection may be ignored, as the driver is perceived to have a low tendency to experience motion sickness. It should also be noted that if the vehicle is a shared or autonomous vehicle not driven by an occupant, the occupant may prefer to trade reduced motion sickness for increased other factors, such as travel time, fuel consumption, or overall comfort. In some embodiments, the vehicle may include a user interface that allows the vehicle occupants to declare their preferences, such as ranking the importance of factors like component wear, comfort, motion sickness reduction, fuel economy, driving duration, and / or safety. In some embodiments, such ranking of factors may be performed entirely or partially by a microprocessor-based controller.

[0029] Depending on the embodiment, special vehicle characteristics, such as the low ground clearance of a sports car, may be taken into consideration in route selection or recommendation. Vehicles with low ground clearance may be more susceptible to damage from, for example, sharp road transitions or speed bumps, and vehicles with low-profile tires may be more susceptible to damage from, for example, potholes. Therefore, route guidance for such vehicles may take into account road components and the types of events that may be encountered. Using a map layer containing such road information, depending on the embodiment, route selection or recommendation may be at least partially customized for a given vehicle or type. Such selection may be based on road ratings for each vehicle type or class.

[0030] The inventors further recognized that the curvature of a road section can be useful information for controlling vehicles and vehicle systems. In some embodiments, the curvature of a road section may be estimated or determined by using crowdsourced data collected from multiple vehicles and / or over multiple trips of that road section by a single vehicle, when a vehicle may be passing through the road section. As used herein, the term “road curvature” refers to the curvature in the direction parallel to the road surface, usually associated with the “yaw” degree of freedom of a vehicle traveling on a road section. Road curvature can be used to determine the in-plane trajectory that a vehicle may take to follow the road. Its value can be used to evaluate the inputs that a driver (or autonomous vehicle controller) may provide and to determine any deviation from these inputs. As used herein, the term “average road curvature at a point” refers to the average curvature of a path taken by two or more instances in which a vehicle passes through a given point on a road section in a given direction without changing lanes or driving erratically. The average road curvature at a given point can be calculated by collecting route and direction information from all or a portion of vehicles traveling on a given road section over a given period of time.

[0031] The inventors recognized that, in some embodiments, the calculation of curvature may be possible from simple latitude and longitude information of a given road section on a map, but in practice, this information is usually not of sufficient quality, resolution, and / or accuracy to distinguish between actual and typical road section transitions and sharp curves. For example, a road map cannot take into account how an actual vehicle may travel along a given road section. For example, the curvature of many sharp curves on a map may be considerably gentler in reality, for instance, because a driver or autonomous controller may "not turn properly" around a curve to reduce the lateral acceleration felt by the occupants at a given speed. In some embodiments, by using a crowdsourced method to record all or a portion of the yaw rate, speed, and lateral acceleration for the involved vehicle traveling through a given road section, along with GPS information and / or other location methods, the average vehicle direction of travel can be determined, for example, at a subset of points along each road section on a map. In some embodiments, the average direction of travel can be determined by adding the sine of the direction angle of a given vehicle at a given location for travel to the sum of the sine of the direction angles of all or a suitable subset of vehicles passing through the same location, separately adding the cosine of the direction angle of a given vehicle at the same location for travel to the sum of the cosine angles of the vehicle's direction angles, or to all or a suitable subset of vehicles passing through the same location, and then calculating the average angle using the ratio of the sum of sine to the sum of cosine. This method may be equivalent to calculating the angle of the vector sum of normalized direction vectors for a selected subset of each passage or crossing at a given location on a road.

[0032] In some embodiments, having information about the mean curvature of the road ahead allows the expected lateral acceleration to be estimated for any given speed, and an optimal speed to be selected. This can be useful, for example, when a reduction in speed is necessary to properly navigate an upcoming curve because the expected lateral acceleration at the current speed may exceed the safety limits under the current road or weather conditions, and / or the acceleration would exceed the comfort limits for the occupants, and / or the change in acceleration is perceived as too abrupt and therefore could create a perception of a lack of safety or comfort. Alternatively, or in addition, information about road curvature may be used to control the roll of the vehicle body at a given speed, for example, by adjusting the damping rate of one or more semi-active dampers, or by applying active or passive forces using one or more active suspensions or active roll control actuators. In some embodiments, determining the optimal or desired speed may also be based on expected weather conditions at the curve. For example, the effects of ice, snow, rain, and / or wind may be considered. In some embodiments, access to road curvature and weather information may help select an appropriate speed to avoid spin-out. Autonomous and / or driven vehicles may benefit from such information. Depending on the embodiment, information regarding road curvature may also be used by navigation or control systems in route selection or recommendation.

[0033] In some embodiments, information regarding the road curvature of a preceding road section may be combined with information regarding the road grip of one or more of the vehicle's tires to determine a safe limit for driving speed for a particular vehicle under a given set of road surface conditions. In some embodiments, the road grip information may be based on data from multiple sources, including, for example, measurements from a municipal road assessment, crowdsourced information from an on-board grip estimator of a preceding vehicle, information regarding road roughness (e.g., focusing on roughness within a tire hop frequency of, for example, 12 Hz (or in the range of 10-15 Hz) at a given driving speed), and information regarding road surface changes based on recently traversed road sections and / or based on a crowdsourced method from vehicles that have recently traversed the upcoming section, which may indicate snow or ice on the road. By combining some or all of these information sources, for example, from crowdsourced methods as described above, or simply from road curvature knowledge from road section maps, and / or vehicle information, the maximum safe driving speed can be determined with some margin to avoid inducing the driver or autonomous driving operator to take excessive risks. In some embodiments, the control system may provide such information indirectly (for example, through warning lights, head-up displays, or vehicle display functions, or, for example, on a phone app used for navigation) or directly (by communicating with the vehicle's computer responsible for speed control, such as a cruising control system, anti-lock braking system, vehicle domain controller, or, in the case of an autonomous vehicle, a driving controller). This limit speed may be a more accurate representation of the maximum safe speed for a road section than posted speed limits provided by road maintenance personnel, local authorities, or national authorities managing the roads. In some embodiments, the method may take into account conditions that can change rapidly and / or may be specific to a particular vehicle, such as location, weather, road roughness, and tire grip conditions.For example, the recommended maximum speed, determined by a microprocessor-based controller for a particular vehicle traveling a specific section of road under a specific set of weather conditions, may be based on information about the vehicle's suspension system (e.g., as inferred by its transfer function), the state of one or more of its tires, the vehicle's load, and / or its center of gravity, as well as other factors.

[0034] It should be noted that the expected lateral acceleration for a given road section may depend on the driving speed. If the driving speed can be estimated fairly accurately based on the speed limit and current traffic conditions, this allows for estimation of the amount of lateral acceleration that will be encountered during a given journey. Lateral acceleration can be a factor both in terms of overall occupant comfort and the potential to induce motion sickness, as well as a factor in wear on vehicle components, such as tires, bushings, and dampers. For example, if the selection is between a first route to a destination and a second route that includes sections with higher lateral acceleration than the first route, the first route with lower lateral acceleration may be chosen, for example, at the expense of increased travel time, in order to reduce discomfort, occupant motion sickness, and / or tire wear. Depending on the embodiment, the selection or recommendation of a route and / or speed may also depend on activities that one or more occupants may be engaging in. For example, based on information that one or more occupants are typing on a keyboard, using a computer mouse, and / or writing on paper, or are likely to be doing so, the vehicle speed and / or route may be selected to keep the lateral acceleration below a predetermined limit.

[0035] Depending on the embodiment, certain vehicles (e.g., trailer-hawing vehicles such as large trucks or personal vehicles towing recreational trailers, and vehicles with long wheelbases such as recreational vehicles (RVs)) may encounter more severe difficulties due to sharp curves on the road. Depending on the embodiment, advance notice may be provided to such vehicles, and / or certain routes or sections of the road may be avoided entirely. Depending on the embodiment, navigation guidance and recommended speed limits for such vehicles or other vehicles that encounter difficulties due to sharp curves or increased lateral acceleration for kinetic or comfort reasons may be based at least in part on the expected or predicted lateral acceleration.

[0036] Depending on the embodiment, the mean curvature at a given point on a given road section may also be used to accurately and with minimal waiting time predict lane departure or lane change by, for example, comparing the current curvature of the path being followed by the vehicle with a previously determined mean or predicted curvature for that section. Since the initial step in changing lanes may be a change in direction of travel before a lateral deviation occurs, this enables immediate or effectively immediate recognition of a deviation from the path, as opposed to methods of recognizing lateral deviations from the path (e.g., methods based on visual recognition of lane markings or methods based on recognizing the road terrain). Often, vision systems or other similar systems cannot provide road curvature information, for example, when visibility may be poor due to weather or lighting, when road signs may be inadequate, or when the actual driving route taken by most drivers deviates from road signs. For example, sensors that may be used to assist navigation may be hindered or disabled during adverse weather conditions (e.g., fog or snow), and / or when debris or mud may be present on the road, and / or when faded or absent lane markings make lane recognition difficult. Using the vehicle's current estimated direction of travel and comparing it to the mean direction of travel (or using the current curvature and comparing it to the mean curvature) allows for the identification of any significant deviation from the expected path. For example, a significant deviation in direction of travel may be 1 to 3 degrees or more, and the integral of the distance of the deviation in direction of travel can be used to determine the resulting lateral offset, thus allowing for the estimation of the number of lanes crossed during steering. The same technique can also be applied to determine when a vehicle is entering one road from another, or when a vehicle may be entering an exit lane that may be parallel to the normal driving lane. Determining when a vehicle may be in an exit lane can be useful on main roads where GPS resolution may be insufficient to recognize when a driver enters an exit lane (or conversely, when a driver should have been in an exit lane but did not exit).

[0037] Depending on the embodiment, information about the road section (e.g., road profile, road curvature, road grip, and / or current weather conditions) may be used, along with information about the vehicle (e.g., geometry, center of gravity, type, suspension system capabilities (e.g., transfer function), and / or dynamic capabilities), vehicle components (e.g., tire type and wear and / or damper type and wear), and other relevant information, to calculate one or more of the recommended average speed, recommended instantaneous speed, maximum recommended speed, and minimum recommended speed.

[0038] The recommended speed may be useful as a guideline for the driver or as input to an autonomous or semi-autonomous vehicle operating system or controller. For example, the recommended speed may deviate from the speed limit on a given road due to current road conditions (e.g., low grip due to rain or snow), the type and condition of one or more of the vehicle's tires (e.g., one or more heavily worn tires), or the road profile or type of road (e.g., a road in poor condition or with small undulations that can cause the vehicle to skid, or a road with numerous low-frequency bumps that can cause certain types of vehicles to lose lateral grip), or the type of vehicle (e.g., a long wheelbase and / or high center of gravity vehicle such as a bus or SUV that may have a lower safe lateral acceleration limit).

[0039] In some embodiments, the recommended maximum speed for a road section may be below the posted speed limit on the road to which the section may be part, while the recommended minimum speed may be useful on road sections where passing over road components at higher speeds over lower speeds may result in fewer complaints or cause less damage to the vehicle or discomfort to the vehicle occupants. For example, passing over speed bumps at excessively low speeds may cause exaggerated vertical motion, e.g., discomfort and / or motion sickness, while passing over them at excessively high speeds may cause, e.g., damage to the vehicle or its components. In such circumstances, a speed range between the minimum desirable speed and the maximum safe speed may be recommended. In some embodiments, information regarding posted speed limits for a particular type of vehicle may be obtained, and the recommended maximum speed may be less than or equal to the posted speed. In some embodiments, the recommended maximum speed may also be a function of vehicle weight per axle, for example, to minimize damage to the road surface.

[0040] In some embodiments, the recommended speed may be based on the vehicle's dynamic characteristics. Depending on the vehicle's wheelbase and track width, certain types of road inputs may be worse than others at some speeds. For example, the vehicle's wheelbase determines what spatial frequency inputs to the vehicle produce heave vibrations, where the front and rear of the vehicle move up and down to the same extent, or pitch vibrations, where the front and rear of the vehicle move out of phase. For example, a ground rift that may be significantly longer than the vehicle's wheelbase may excite heave motion, or only heave motion, while a ground rift with a wavelength equal to twice the wheelbase may induce pitch motion. The inventors, however, recognized that the frequency of disturbances to which the vehicle may be exposed can be determined by the vehicle speed. Given the vehicle's dynamic characteristics, there are therefore speeds that can excite, for example, heave, roll, or pitch resonance, or a combination of two or more types of resonance, within the vehicle. For example, in some embodiments, disturbances may excite a primary heave resonance in a vehicle at a specific speed or range of speeds, in which case the vehicle's motion may become particularly prone to complaints. Therefore, it may be desirable to avoid driving at speeds that excite the vehicle's dynamic characteristics in any given direction of motion, for example, driving at speeds that produce input frequencies that excite the vehicle in a manner that may lead to complaints, on roads with many road components at wavelengths close to the vehicle's wheelbase. In some embodiments, such speeds may be avoided when recommending a driving speed. For example: 1. The first road section may have a sinusoidal spatial road profile with a wavelength of 6 meters, in common mode (meaning the road surface profiles on the left and right sides below the vehicle are similar). 2. The first vehicle may respond poorly to a pitch input at 1.5 Hz, for example, due to dynamic resonance.

[0041] If the first vehicle travels along the first road section in the above example at a speed of Vx = 20.1 mph = 9 m / s, then the sinusoidal road described above will produce a pitch input at frequency f = 9 m / s / 6 m / cycle = 1.5 cycles / second = 1.5 Hz. If the vehicle is sensitive to a pitch input frequency of 1.5 Hz, it may be desirable to avoid traveling along this first road at a speed of 20 mph or nearby. If the same vehicle is, for example, much less sensitive to a pitch input at 3 Hz, then a driving speed of 40 mph may be more desirable, as it will produce a pitch input at f = 40 * 1.6 / 3.6 / 6 = 2.96 Hz. At the same time, if a vehicle with a longer wheelbase of 4.5m travels the same road, it will not generate significant pitch input and therefore cannot be sensitive to the pitch component of this road section (while being sensitive to other components at different driving speeds, resulting in different recommended, maximum recommended, or minimum recommended speeds).

[0042] In some embodiments, the effects of wheel imbalance can be mitigated by selecting the vehicle speed. The inventors recognized that the wheels of a road vehicle rotate at a speed that can be calculated based on their effective rolling radius and the vehicle's forward speed. Due to the dynamic characteristics of tires, the effective rolling radius of a tire is generally slightly smaller than the actual free radius but larger than the tire's compression radius. The radius of a fully inflated tire can be, for example, 338 mm, and the height of the wheel center above the ground with the vehicle weight on it can be significantly smaller, for example, 315 mm (which can be called the tire's "compression radius"), but the distance traveled by the wheel center for each full rotation of the hub can be 330 mm (which can result in an effective tire radius of approximately 52.5 mm). Under typical driving conditions, when the vehicle is not accelerating, turning, or decelerating, wheel slip can be little to no, and may be less than 1%, for example. As used herein, the term "wheel slip" refers to the difference between the vehicle's forward speed and the product of the wheel's effective rolling radius and its angular velocity.

[0043] In some embodiments, the suspension and associated tire at a given corner may be designed to have a resonant natural frequency, often referred to as tire hop or wheel hop. This resonant frequency may be a characteristic of the unsprung mass system (which, in an independent suspension, may be equal to the mass of the wheel and any combination of related moving components of the suspension kinematically linked to move with the vehicle chassis, and in a non-independent suspension, may be defined according to the dynamic characteristics governing that type of suspension and wheel). The inventors recognized that the tires of a vehicle function primarily and effectively as springs in the vertical direction, with light damping in the vertical direction (i.e., they do not dissipate large amounts of energy when compressed and restored by inputs applied by the road surface in a direction that may be perpendicular to the road surface) in order to minimize energy loss during rolling. Therefore, the resonance of the unsprung mass combined with the tire spring can be very pronounced, for example, with a resonance peak that can be 5 to 10 times larger than the underlying response. During resonance, the wheel can be excited and bounced considerably when exposed to an input at or near the tire hop frequency, for example, at 12 Hz or in the range of 10 to 15 Hz for a typical vehicle.

[0044] In some embodiments, tires and wheels can rotate at high speeds (for example, when traveling at 60 mph with a tire having an effective rolling radius of 318 mm, the wheel may be rotating at 5055 rpm), and therefore any minor defect in the tire or wheel, such as the equivalent of an eccentric mass of 10 g added to the rim at one point, can cause a significant vertical force disturbance that can be applied to the unsprung mass. For this reason, wheels are often balanced using a small countermass, and sometimes the force is balanced using the resultant force measured between the wheel and the measuring device. In some embodiments, one or more wheels may remain unbalanced, and as they rotate, this unbalanced state can induce vibrations in the forces applied to the tires and suspension. For example, a defect in the mass distribution on the wheel or rim, resulting from a curb collision that slightly bends the rim, can cause a change in the force in the vertical load each time that point on the rim approaches the road. Depending on the embodiment, any mass imbalance on a tire or wheel, which may result from the loss of one or more countermasses applied by a technician when mounting the tire, can generate a centripetal force directed towards the center of the wheel, which depends on the order of the square of the rotational speed and may be directed vertically upward by 1 degree for each rotation of the wheel. Therefore, the input of these types of forces may occur at a frequency that is proportional to the vehicle's operating speed and proportional to the amount of defect present on each wheel.

[0045] The inventors recognized that the amount of defect in each wheel can be estimated by analyzing the spatial frequency component (the reciprocal of the wavelength as a function of distance traveled) of the vertical acceleration of each wheel. In some embodiments, the frequency component of the vertical acceleration of each wheel as a function of time can be analyzed. The inventors recognized that both quantities can be used, for example, as diagnostic tools to determine the condition of specific components within a vehicle. For example, a large change in tire hop frequency, e.g., a change of 1 Hz or more, may indicate a tire problem, while a large change in imbalance on a given wheel may be a leading indicator of possible damage to the tire or tread that could require repair and potentially cause a rupture. In addition, an unbalanced wheel driven at a speed that excites its natural frequency can cause considerable vibration within the vehicle that may be perceived by the occupants, so this information can be used to provide the driver or vehicle controller with guidance on which speed may be optimal for comfort. The inventors recognized that under certain conditions, this discomfort can be effectively reduced by driving at higher or lower speeds.

[0046] Depending on the embodiment, one or more systems within a vehicle may report to the customer, vehicle occupants, and / or the vehicle owner or operator regarding the ride comfort experienced on a given trip. This can be done in multiple ways, for example, firstly by analyzing measured vehicle motion; secondly by analyzing the road profile traversed by the vehicle based on the known or estimated shape of the road as seen by the vehicle; and thirdly, favorably, by comparing the measured vehicle motion with the expected motion based on the traversed road components and the optimal vehicle behavior model. This can enable estimation of the vehicle's condition, estimation of any deterioration in the vehicle, and estimation of discomfort experienced by the occupants. It can enable estimation of the amount of vibration experienced by cargo, which can be an indicator of quality for special types of cargo, for example, fresh produce or fragile electronic equipment. The method can also be applied intrinsically, as described above, to provide optimal route guidance based on estimated road components at a given speed and estimation of their expected impact on a given cargo being transported. For example, a cargo of fresh strawberries may be particularly sensitive to vibration levels that could damage the fruit. In some embodiments, the inventors recognized that by knowing the road profile, expected driving speed, and at least an estimated model of the vehicle, the vibration levels to which the cargo may be exposed while traveling along a given route can be predicted a priori. In some embodiments, such information may also be used to provide intelligent route guidance to optimally protect the cargo.

[0047] Depending on the embodiment, a general driver profile may be created based on one or more possible inputs. For example, a driver profile may be generally tailored to the vehicle being driven (for example, a sports car may have a more aggressive initial driver profile than a compact car), and the driver may provide identification in the form of login, or some other form of identification such as facial recognition, fingerprint ID, or connection to a mobile phone, in order to access the stored personal profile, and pre-programmed settings may take into account external information such as time of day, type of road being driven, weather and other environmental factors, as well as historical data based on commute routes and typical driving.

[0048] The driver profile may be designed to remember personal (or general) preferences related to the relative importance of total driving time to other factors, such as comfort, vehicle wear or damage, and other factors listed above. This information may be explicitly provided by the vehicle's driver or occupants, or automatically collected by vehicle sensors during previous trips.

[0049] Depending on the embodiment, actual current conditions and driver behavior may be used to modify, update, or generate a driver profile for the current driver. Multiple observed and measured entities may be considered. For example, if a driver frequently changes lanes, drives at a higher speed than usual or higher than most other drivers, or otherwise implicitly indicates that they are trying to get to their destination faster, then driving time may automatically take precedence over comfort. Similarly, using the driver's or other passengers' identification or logon authentication information and / or their electronic calendars, the navigation-assistance controller or other microprocessor-based controller may consider when and where the next calendar events will occur and request, or automatically do, to modify the driver's preferences to relatively increase or decrease the prioritization of driving time in favor of other considerations such as comfort, toll costs, motion sickness, or vehicle wear or damage. Alternatively, if it can be assumed, based on time, direction of travel, and / or location, that the driver is commuting to and from work, then, for example, the importance of wear and tear or cumulative vehicle damage may be given a relatively higher or lower priority relative to the travel time, while during long-distance trips, the importance of motion sickness reduction and comfort may increase.

[0050] Depending on the embodiment, one or more of the methods described above may be combined. The multiple factors presented above may be combined into a single metric that enables the system to rank travel routes according to such a combined metric and select the optimal one.

[0051] In some embodiments, the metric may be based on a combination of multiple factors. Each factor may be scaled to a relative scale of 0 to 1, where 1 is considered the highest value and 0 is considered the lowest value. For example, when considering tire wear, a scaling factor of 0 may be assigned to road components that do not cause a significant increase in tire wear beyond that of a perfectly flat road, such as a very low component near the tire hop frequency, while a scaling factor of 1 may be used for roads that can accelerate tire deterioration by 1.5 to 3 times. In addition, or alternatively, in some embodiments, the factor for motion sickness may be set to 0 for flat roads or when no occupants are highly susceptible to motion sickness, and to 1 for roads that are likely to induce noticeable nausea in at least one occupant during half an hour of driving. The scale for each factor may be set, for example, by the system designer, the vehicle manufacturer, or the road profile tool manufacturer. In some embodiments, relative weighting may be applied to one or more factors. This weighting may be based on the aforementioned considerations, as well as general and sometimes specific driver profile considerations, along with knowledge of the type, condition, and history of a given vehicle and its components. In some embodiments, a total value may be determined for each road section by using a value-based weighting, multiplying the weight by a scaled value for each factor, and summing all factors. In this way, an optimized route plan may be achieved, and the optimal may be determined based on a subset of several factors, each having a weighting coefficient that can be modified based on personal preferences or some of the aforementioned considerations. In some embodiments, this total value may be used as a metric to rank road sections against each other and select the route with the lowest total score as the optimal for the current driver, vehicle, road conditions, and traffic, and / or current circumstances.

[0052] Depending on the embodiment, a number of pre-selected combinations of weights, combined to prioritize combinations aimed at a specific purpose, such as driving enjoyment (thus weighting high curvature and high-speed roads as important factors, and comfort and motion sickness as less important), comfort (thinking comfort and motion sickness as important factors, and driving time as less important), economy (thinking fuel consumption and component wear as important factors, and other factors as less important), or even "I'm slow" (prioritizing driving time over all others), or "I'm tired" (prioritizing roads with less curvature and fewer curves), may be presented to the driver as choices, for example, via a user interface or graphical interface in the vehicle or on a device such as a cell phone.

[0053] Depending on the embodiment, weighting may be set by the consumer, for example, via a user interface or cell phone, in an individualized manner for each factor or for groups of factors, and these weights may be stored in a user profile based on the user's selection or command, or applied only to the current driving session.

[0054] While some of the factors that may be considered are listed above, it should be understood that other factors may also be considered. Factors listed above include: driving time, (current or expected) traffic conditions, local weather conditions, road grip, expected grip at expected driving speed, recommended speed (as opposed to speed limits or current traffic speed), traffic lights, lane changes (left turns in countries like the United States), pedestrian crossings, tolls, narrow or cramped roads, spatial frequency road components, expected comfort level, comfort history over the current drive, expected component wear, current state of component wear, number and type of road events, overall discomfort, fuel consumption, occurrence of motion sickness, minimum ground clearance issues, road curvature, expected lateral acceleration due to road shape and curvature, wheel imbalance, and the tendencies of each road that excite it at the currently expected driving speed, cargo type and the cargo's sensitivity to vibration, general driver profile, current or changed driver profile, and customer preferences.

[0055] Depending on the embodiment, a cost function may be used to quantify the occurrence and / or severity of certain undesirable effects associated with traveling along a route from a first point to a second point. Undesirable effects may include, but are not limited to, motion sickness, wear of vehicle components (e.g., tire wear, bushing wear, and damper wear), and inefficiencies. When a vehicle with occupants travels on a road surface, a cost function may be associated with the operation of the vehicle. Such a cost function may be related to, or a function of, vehicle-specific data, such as (i) road-specific data, e.g., road surface data and / or risk factors, or (ii) transfer functions or models of the vehicle's suspension system, braking system, steering system, or wear models of various components such as springs, dampers, bushings, or tires. The cost function may be developed in a laboratory through computer simulations based on crowdsourced data and / or information provided by component or vehicle manufacturers. When faced with the choice of several routes to travel between a first point and a second point, the chosen route may be the one with the lowest cost function.

[0056] Although this instruction has been described in relation to various embodiments and examples, it is not intended to be limited to such embodiments or examples. On the contrary, as will be understood by those skilled in the art, this instruction encompasses various alternatives, modifications, and equivalents. Accordingly, the above description and drawings are merely illustrative examples.

[0057] Embodiments in which the technique is implemented in the form of circuit mechanisms and / or computer-executable instructions have been described. It should be understood that some embodiments may be in the form of methods, for which at least one example is provided. The actions performed as part of the Method may be ordered in any preferred manner. Thus, embodiments in which actions are performed in a different order than those illustrated may be constructed. This may include performing some actions simultaneously, even if they are shown as sequential actions in the illustrative embodiments.

[0058] Various aspects of the embodiments described above may be used individually, in combination, or in various configurations not specifically discussed in the embodiments described above, and therefore, their application is not limited to the details and arrangement of components described in the above description or shown in the drawings. For example, an aspect described in one embodiment may be combined in any way with an aspect described in another embodiment.

[0059] The use of ordinal terms such as "first," "second," "third," etc., in a claim to modify a claim element does not, in itself, imply any priority, rank, or order of the claim element relative to another, or a temporal order in which the actions of the method are performed, but merely serves as a label to distinguish one claim element having a particular name from another element having the same name (if the ordinal terms are not used).

[0060] Furthermore, the terminology and technical terms used herein are for illustrative purposes only and should not be considered limiting. The use of “including,” “having,” “containing,” “involving,” and variations thereof herein is intended to encompass the items listed therein, their equivalents, and additional items.

[0061] The word “exemplary” is used herein to mean an example, example, or illustration. Therefore, any embodiments, implementations, processes, features, etc., described herein as examples should be understood as illustrative examples and not as preferred or advantageous examples unless otherwise stated.

[0062] Having described several aspects of at least one embodiment, it should be understood that those skilled in the art will readily conceive of various modifications, changes, and improvements. Such modifications, changes, and improvements are intended to be part of this disclosure and are intended to be within the spirit and scope of the principles described herein. Accordingly, the above description and drawings are merely examples.

Claims

1. A method of operating a vehicle, wherein the said method The controller receives road surface information regarding at least two routes between the first location and the second location, The controller receives vehicle-specific information, including information regarding the transfer function of the vehicle's suspension system. The controller selects a route from among the at least two routes, wherein the selection is based on the information received by receiving the road surface information and at least partially the vehicle-specific information, and The vehicle will travel along the selected route, A method that includes this.

2. The method according to claim 1, wherein the at least two routes include a first route and a second route, and the first route and the second route overlap each other at least partially.

3. The method according to claim 1 or 2, further comprising receiving information relating to the location of the vehicle, wherein the location of the vehicle is determined using a location system selected from the group consisting of GNSS and terrain-based location systems.

4. The method according to claim 3, wherein the location of the vehicle is the first location.

5. The method according to any one of claims 1 to 4, wherein the vehicle is selected from the group consisting of autonomous vehicles and semi-autonomous vehicles.

6. The method according to any one of claims 1 to 5, wherein the suspension system of the vehicle is an active suspension system.

7. The method according to any one of claims 1 to 6, wherein the information received includes information relating to the position of the center of gravity of the vehicle.

8. The method according to any one of claims 1 to 7, further comprising receiving information regarding the estimated speed of the vehicle when it is traveling along at least a portion of the at least two routes.

9. The method of claim 8, further comprising determining estimated road-induced disturbances while traversing the at least two or more routes, based at least partially on the road surface information while passing through at least a portion of the two or more routes, and at least partially on the estimated speed of the vehicle, wherein the selection of a route from the two or more routes is also at least partially based on the estimated road-induced disturbances.

10. The method according to claim 9, wherein the received vehicle-specific information includes information relating to the weight of the vehicle.

11. The method according to any one of claims 1 to 10, wherein the received vehicle-specific information includes information relating to at least one vehicle occupant.

12. The method according to claim 11, wherein the information relating to the at least one vehicle occupant includes information relating to the sensitivity of the at least one vehicle occupant to motion sickness.

13. The method according to claim 11, wherein the information relating to the at least one vehicle occupant includes information relating to the at least one vehicle occupant's susceptibility to motion sickness while performing an activity selected from the group consisting of reading and operating a computer mouse.

14. The method according to claim 11, wherein the received vehicle-specific information includes information relating to estimated activities by at least one vehicle occupant.

15. The method according to any one of claims 1 to 14, further comprising determining a range of operating speeds while traveling along the route based on the information received and at least partially received vehicle-specific information in receiving road surface information, and traveling on the road surface within the determined operating speed range.

16. A method of operating a vehicle, wherein the said method The controller receives road surface information for at least two routes between the current location and the destination, The controller receives vehicle-specific information relating to the vehicle, and this vehicle-specific information includes information regarding the transfer function of the vehicle's suspension system. Based on the information received from the controller, including road surface information and vehicle-specific information, a route is selected from the at least two routes in order to achieve an effect selected from the group consisting of less wear on components, less motion sickness, shorter travel time, and higher energy efficiency. To travel along the selected route, A method that includes this.

Images