JPWO2012160593A1 - Parameter estimation method, characteristic evaluation method, and navigation apparatus - Google Patents

Abstract

  A parameter E that defines the energy consumption factor of the vehicle in each section based on the traveling state of the vehicle in each section on the route and the route information in each section, and the weighting of the energy consumption corresponding to the parameter E in each section Based on the given parameter C, the parameter C is estimated based on the relational expression of the energy consumption model expressing the energy consumption Q of the vehicle traveling on the route.

Description

  The present invention relates to a parameter estimation method for estimating a parameter that gives a weight of an energy consumption amount corresponding to an energy consumption factor of a moving body such as a vehicle, and the operation of the moving body or the moving body itself using the parameter estimated by this method. The present invention relates to a characteristic evaluation method for evaluating characteristics, and a navigation device for searching for a route in consideration of energy consumption calculated using parameters estimated by this method.

  In order to search for a route with the minimum energy consumption, it is necessary to predict the energy consumption during traveling for a road segment on the route. For example, in Patent Document 1, an estimation method for estimating a propulsive force-related operation parameter unique to a vehicle or a driver thereof using vehicle travel data and a route search using the estimated propulsion-related operation parameter are performed. A navigation system is disclosed.

  In the estimation method disclosed in Patent Document 1, a driving phase such as rest, start, and low-speed driving is estimated, and vehicle-specific parameters such as a rolling drag coefficient of the vehicle related to each driving phase are estimated. Then, using the estimated vehicle-specific parameters, driving force-related operation parameters such as fuel consumption, energy consumption, and carbon dioxide emission are estimated.

JP 2010-190895 A

  In the estimation method described in Patent Document 1, a vehicle-specific parameter is estimated using a vehicle model corresponding to a traveling phase. Therefore, it is necessary to collect travel data according to each travel phase, and further, a different model for the vehicle subsystem according to the travel phase is required. For this reason, there existed a subject that the calculation cost required for parameter estimation increased.

  Further, in Patent Document 1, since travel data for each travel phase is required, the amount of travel data to be collected inevitably increases. For example, when estimating driving force-related operation parameters of different drivers, it is necessary to collect travel data corresponding to each driver for each travel phase. Therefore, it is not possible to flexibly cope with a change in the situation that affects the energy consumption of the vehicle such as a difference in drivers.

  Furthermore, since the estimation method described in Patent Document 1 indirectly estimates the propulsive force-related operation parameter using a model corresponding to information related to vehicle propulsion such as torque and engine rotation speed, Detailed travel data such as torque, gear, and brake pressure are required.

  The present invention has been made to solve the above-described problems, and can estimate a parameter that gives a weight of energy consumption corresponding to an energy consumption factor of a moving object while reducing the calculation cost. A parameter estimation method capable of flexibly responding to changes in the situation affecting consumption, a characteristic evaluation method for evaluating the operation of the moving body or the characteristics of the moving body using the parameters estimated by this method, and the estimation using this method It is an object of the present invention to obtain a navigation device that performs navigation processing in consideration of energy consumption calculated using the parameters.

  The parameter estimation method according to the present invention includes a first parameter that defines the energy consumption factor of the moving body in each section based on the moving state of the moving body in each section on the route and the path information of each section, Based on the relational expression of the energy consumption model that expresses the energy consumption of the mobile body that has moved along the route from the second parameter that gives the weight of the energy consumption corresponding to the first parameter of the section, the second parameter Is a parameter estimation method for estimating the parameters of the vehicle, wherein the history information acquisition unit indicates the energy consumption amount of the mobile body consumed by moving the route, the route information of the route, and the moving state of the mobile body on the route The movement history information including the information is acquired, and the parameter estimation unit determines the first parameter based on the route information included in the movement history information acquired by the history information acquisition unit and the movement state of the moving body. Based on the relational expression of the energy consumption model using the energy consumption amount of the moving body included in the derived first parameter and the movement history information, the second parameter in each section on the route is derived. Estimate the parameters.

  According to the present invention, it is possible to estimate the parameter that gives the weight of the energy consumption corresponding to the energy consumption factor of the mobile body while reducing the calculation cost, and to flexibly cope with the change in the situation that affects the energy consumption. There is an effect that can be.

It is a block diagram which shows the structure of the navigation apparatus which concerns on Embodiment 1 of this invention. 3 is a flowchart showing a flow of parameter estimation processing by a parameter estimation unit according to Embodiment 1. 6 is a conceptual diagram of parameter estimation according to Embodiment 1. FIG. 4 is a flowchart illustrating a flow of route search processing by the navigation device according to the first embodiment. It is a block diagram which shows the structure of the navigation apparatus concerning Embodiment 2 of this invention. 10 is a flowchart illustrating an example of a driving characteristic evaluation process by a characteristic evaluation unit according to the second embodiment. 6 is a flowchart illustrating an example of a vehicle characteristic evaluation process performed by a characteristic evaluation unit according to Embodiment 2.

Hereinafter, in order to describe the present invention in more detail, modes for carrying out the present invention will be described with reference to the accompanying drawings.
Embodiment 1 FIG.
FIG. 1 is a block diagram showing the configuration of a navigation device mounted on a mobile body (for example, a vehicle) according to Embodiment 1 of the present invention. In FIG. 1, a navigation device 1 uses a travel history information of a vehicle (hereinafter referred to as “own vehicle”) on which the navigation device 1 is mounted, based on an energy consumption model described later, a road section (a road link defined by map data). ) To estimate the parameter that gives the weight of energy consumption corresponding to each energy consumption factor, and to apply the estimated parameter to the navigation process. The parameter that gives the weight of the energy consumption corresponding to the energy consumption factor is a parameter of the energy consumption model handled in the present invention, and details thereof will be described later.

The navigation device 1 includes, as its configuration, a travel history information acquisition unit 2, a travel history information storage unit 2a, a vehicle information acquisition unit 2b, a parameter estimation unit 3, a link cost calculation unit 4, a route search processing unit 5, and a user input unit 6. And a map database (DB) 7.
The travel history information acquisition unit 2 is a history information acquisition unit that acquires travel history information used for estimating the parameters from the travel history information storage unit 2a. The travel history information includes information on the travel route of the vehicle, for example, travel time, travel speed, stop, acceleration / deceleration of the vehicle, and energy consumption in travel of the travel route.
The travel history information storage unit 2a is a storage unit that stores travel history information, and stores travel history information in association with the driver and the traveling vehicle.
The vehicle information acquisition unit 2b is a configuration unit that acquires vehicle information of the host vehicle, and includes a sensor that measures vehicle information stored as travel history information and a vehicle control unit. The vehicle information includes actual measurement data such as the position of the host vehicle, the traveling speed of the host vehicle traveling on the route, acceleration / deceleration, stop, energy consumption, and the like.

  The parameter estimation unit 3 uses the travel history information related to the processing target travel route acquired by the travel history information acquisition unit 2 and the map data of the travel route in the map DB 7, and uses the road section of the travel route according to the energy consumption model described later. A weighting parameter for each energy consumption is estimated. The link cost calculation unit 4 relates to the energy consumption amount for each road section in the travel route to be processed from the weighting parameter of the energy consumption amount for each road section estimated by the parameter estimation unit 3 and the corresponding road data in the map DB 7. It is a component which calculates a link cost.

  The route search processing unit 5 is a route search unit that searches for a route that minimizes the energy cost connecting the start point and the end point based on the link cost related to the energy consumption for each road section calculated by the link cost calculation unit 4. . The user input unit 6 is a component that receives a setting input of a start point (for example, a departure point) and an end point (for example, a destination) by a user, and is realized by, for example, a touch panel mounted on the screen of a display device. The map DB 7 is a database that stores map data used in navigation processing such as route search. The map data includes, for example, road data indicating a node, a road link connecting the nodes, a road type that is a road attribute of the road link, an elevation difference of the road link, and the like.

Here, the energy consumption model handled in the present invention will be described.
The travel time in the jth road section on the travel route i is T _ij, and the link distance that is the length of the road section is D _ij . These are specified from the traffic characteristics on the travel route i, that is, the traveling state of the own vehicle.
Further, the sum of the climbing elevation differences that is the sum of the elevation differences of the climbing road sections in the road section is H _{up_ij,} and the sum of the descending elevation differences that is the sum of the elevation differences of the descending road sections in the road section is H _{down_ij} . These are specified from road data of the travel route i, for example, road attributes.
It is _assumed that the traveling speed of the vehicle in the jth road section on the traveling route i is v _ij , the number of accelerations from the stop of the vehicle in the road section is N _{stop_ij} , and the number of accelerations from the deceleration is N _{decc_ij} . These parameters are specified from the traffic characteristics (traveling state of the host vehicle) on the travel route i.
Furthermore, if the parameters that give the weighting of the energy consumption that is the object of estimation (correction) are C ₁ ,..., C ₇ , the vehicle travels on the jth road section on the travel route i. energy consumption Q _i and the parameters C _1, · · ·, between the C _7, holds the relationship of the following formula (1).
Where q _base is the basic energy consumption per unit time (cc / s or W).
μ is a friction coefficient (−) between the tire of the own vehicle and the road surface, and κ is an air resistance coefficient (−) of the own vehicle.
M is the vehicle weight of the own vehicle, and a value such as 1500 (kg) is set, for example.
m is inertia, for example, a value such as 0.2 · M (kg) is set.
g is a gravitational acceleration, and is set to 10.0 (m / s ² ), for example.
ε is the net thermal efficiency (−), and η is the total transmission efficiency (−).
H is a fuel calorie conversion coefficient, and is set to a value such as 3.4 · 10000 (J / cc), for example.
v _{stop_s} is the speed (= 0 (km / h)) at the start of acceleration from the stop of the _host vehicle.
v _{stop_e} is the speed at the end of acceleration from the stop of the _host vehicle, that is, the travel speed at which the acceleration is stopped from the stop state and the acceleration is terminated. When the travel route i is a highway, for example, 100 (km / h) ) Is set.
v _{decc_s} is the speed at the time of starting acceleration from the deceleration of the _host vehicle, that is, the traveling speed at which the acceleration starts again after decelerating. For example, up to 90 (km / h) when the traveling route i is a highway Set to start accelerating when decelerated.
v _{decc_e} is the speed at the end of acceleration from the deceleration of the _host vehicle. For example, 110 (km / h) is set as the traveling speed at which acceleration is terminated after acceleration from 90 (km / h).

When the portions other than the weighting parameters C ₁ ,..., C _{7 in} each term on the right side of the above equation (1) are expressed as E _i1 ,..., E _i7 , the following equation (2) is obtained. E _i1 ,..., E _i7 are included in the travel time, travel distance, travel speed, number of accelerations, and road data of the travel route i (map data of the map DB 7) included in the travel history information of the travel route i. This is a parameter that can be calculated using the difference in elevation of the road link.
That is, the first term on the right side of the above equation (1) is a parameter that defines an energy consumption factor depending on the travel time in the jth road section on the travel route i.
The second term on the right side of the above equation (1) is a parameter that defines an energy consumption factor depending on the travel distance of the jth road section on the travel route i.
The third term and the fourth term on the right side of the above formula (1) are parameters that define energy consumption factors depending on the altitude difference in the jth road section on the travel route i. The third term is the climb road section. The energy consumption factor depending on the sum of the altitude difference is defined, and the fourth term defines the energy consumption factor depending on the sum of the altitude difference of the descending road section.
The fifth term on the right side of the equation (1) is a parameter that defines an energy consumption factor depending on the air resistance received by the vehicle in the jth road section on the travel route i.
Further, the sixth term and the seventh term on the right side of the above formula (1) are parameters defining energy consumption factors depending on the acceleration / deceleration of the vehicle in the jth road section on the travel route i. Defines the energy consumption factor depending on the number of accelerations since the stop, and the seventh term defines the energy consumption factor dependent on the number of accelerations after the deceleration.
Q _i = C ₁ · E _i1 + C ₂ · E _i2 + C ₃ · E _i3 + C ₄ · E _i4 + C ₅ · E _i5 + C ₆ · E _i6 + C ₇ · E _i7 (2)

上記式（１）〜（３）が、本発明で扱うエネルギ消費量モデルの関係式である。Furthermore, when the travel history regarding ma travel routes (i = ma) is obtained, the relationship of the following formula (3) is established. By solving this equation (Q = EC) with respect to the energy consumption weighting parameter C, a parameter C (C ₁ , C) giving a weighting of the energy consumption corresponding to the energy consumption Q _i measured by actual traveling of the vehicle. .., C ₇ ) can be estimated.

The above formulas (1) to (3) are relational expressions of the energy consumption model handled in the present invention.

Next, the operation will be described.
{1} Estimation of Parameter C FIG. 2 is a flowchart showing the flow of parameter estimation processing by the parameter estimation unit according to Embodiment 1. FIG. 3 is a conceptual diagram of parameter estimation according to the first embodiment. Here, a method for correcting the parameter C of the energy consumption model using the travel history information acquired a plurality of times for the target travel route will be described.
First, the parameter estimation unit 3 uses the actual energy consumption Q _i measured in the actual travel of the vehicle on the travel route i from the travel history information of the travel route i to be processed acquired by the travel history information acquisition unit 2. Is extracted (step ST1).

Next, the parameter estimation unit 3 uses the travel history information of the travel route i and the corresponding map data in the map DB 7 (road data of the travel route i) to calculate the travel time T in the jth road section on the travel route i. _ij , the link distance D _ij which is the length of the road section, the sum of the elevation difference H _{up_ij} which is the sum of the _height differences of the climb road sections in the road section, the sum which is the sum of the _height differences of the descending road sections in the road section the sum of the altitude difference H _{Down_ij,} acceleration number N _{Stop_ij} from the traveling speed v _ij and stopping of the vehicle in the road section, obtains the acceleration number N _{Decc_ij} from deceleration.
The parameter estimation unit 3 calculates the T _ij, D _ij, energy _{H up_ij, H down_ij, v ij} , N stop_ij, using the value of N _{Decc_ij,} represented by the above formula (1) to (3) A parameter E of the consumption model is calculated (step ST2). As described above, the parameter E reflects the road attributes and traffic characteristics of the travel route i.

Next, the parameter estimation unit 3 uses the actual energy consumption Q _i and the parameter E (E _i1 ,..., E _i7 ) to calculate the energy consumption weighting parameter C from the above equations (1) to (3). (C ₁ ,..., C ₇ ) are calculated (step ST3).
For example, as shown in FIG. 3, when a travel history regarding ma travel routes (i = ma) is obtained, the above formulas (1) to (3) are used by using the actual energy consumption Q _i and the parameter E. ) With respect to the energy consumption weighting parameters C (C ₁ ,..., C ₇ ).
Thereby, the energy consumption weighting parameter C (C ₁ ,..., C ₇ ) can be estimated. That is, it is possible to calculate the weighting parameters C (C ₁ ,..., C ₇ ) that reduce the estimation error with respect to the actual energy consumption Q _i .
This corresponds to solving simultaneous linear equations, and a solution that minimizes the error is obtained using a pseudo inverse matrix.

Although the case where the parameter C is obtained as a solution that minimizes the estimation error with respect to the actual energy consumption Q _i using the pseudo inverse matrix in the above equation (3) is shown, the parameter C is obtained by a simpler method. Also good. For example, the suboptimal parameter C may be obtained by limiting the value of the parameter C by fixing the possible range and the discretization unit and performing a full search on the points where the parameter space is limited by discretization. .
In addition, when the number of parameters C increases and the calculation time required for the solution becomes longer, a solution such as a quadratic programming method may be adopted to increase the speed.

As described above, in the parameter estimation method of the present invention, in the energy consumption model represented by the above formulas (1) to (3), the energy consumption Q on the travel route, the travel time on each route, and the travel The parameter E related to the distance may be obtained from the travel history information.
In this case, as shown in FIG. 2, the travel time T _ij , the number of accelerations N _{stop_ij} , and N _{decc_ij} may be obtained using detailed travel history information including the travel speed of the vehicle.
If detailed travel history information cannot be obtained, the travel time T _ij and the number of accelerations are calculated using the road type or the number of traffic lights of the road section (road link) on the travel route i included in the map data. N _{stop_ij} and N _{decc_ij} may be estimated.
In that case, detailed information such as travel speed is not necessary, and the parameter C can be estimated by storing the total energy consumption Q and travel route i for each travel.

{2} Route Search Processing Applying Parameter C FIG. 4 is a flowchart showing the flow of route search processing by the navigation device according to the first embodiment. In particular, route search is performed for parameter C estimated as {1}. The case where it applies to is shown.
First, the travel history information acquisition unit 2 acquires the travel history information of the host vehicle from the travel history information storage unit 2a (step ST1a).
Next, the parameter estimation unit 3 uses the travel history information acquired by the travel history information acquisition unit 2 and parameters C (C ₁ ,..., C ₇ ) based on the above formulas (1) to (3). Is estimated (step ST2a).

  Thereafter, the route search processing unit 5 provides an HMI (Human Machine Interface) for setting a start point and an end point for receiving a setting input using the user input unit 6. Based on this HMI, the user determines the start point and end point of the route (step ST3a). Subsequently, information indicating the start point and end point of the route is set in the route search processing unit 5 based on an instruction from the user to the user input unit 6.

Next, the route search processing unit 5 uses the map data of the map DB 7 to calculate one or a plurality of route candidates connecting the start point and the end point, and for each road section (road link) on the route candidate. In addition, the energy cost is calculated using the value of the weighting parameter C (C ₁ ,..., C ₇ ) of the energy consumption amount of the corresponding road section estimated by the parameter estimation unit 3.
In this way, the route search processing unit 5 searches for a route having a minimum total energy cost among the route candidates connecting the start point and the end point (step ST4a). Thereafter, route guidance is executed with the route of the search result as the recommended route.

In addition, various scenes are assumed for the timing of estimating the energy consumption weighting parameter C. For example, the travel history information of vehicles of representative vehicle types before the shipment of the navigation device 1 according to the present invention is collected, the weighting parameter C of the energy consumption amount of each road section is estimated, and the map data (road data) is supported. At the same time, it is stored in the navigation device 1. The weighting parameter C estimated in advance is used for route search after shipment.
In this case, the weighting parameter C estimated in advance is used as an initial value (default), and the value of the parameter C is set to the own vehicle in the same manner as {1} based on the traveling history information obtained by traveling the own vehicle. You may correct | amend together.
For example, when real-time energy consumption information can be used through the vehicle's CAN (Controller Area Network) or the like, the energy consumption weighting parameter is set in accordance with the characteristics of the vehicle or the driver when the navigation device 1A is used. C (C ₁ ,..., C ₇ ) may be adjusted online.

  Further, the travel history information is selected according to the driver or the travel date and stored in the travel history information storage unit 2a, and the parameter estimation unit 3 uses the travel history information corresponding to the driver or the travel date and time. The weighting parameter C unique to the driver or unique to the date and time such as day of the week or season may be estimated. By doing in this way, the estimation precision of energy cost can be improved and it is possible for the route search process part 5 to search for an optimal route according to a driver | operator or driving | running | working date.

In the above description, the case where the estimated energy consumption weighting parameter C is used for the route search is shown. However, the calculation of the travelable distance with respect to the remaining energy amount when the guide route is determined, or the guide route The energy consumption weighting parameter C may be used for calculating the travelable range with respect to the remaining energy amount when the energy consumption is not determined.
For example, when the guide route is determined, the energy cost of each road section from the current position to the destination is calculated using the energy consumption weighting parameter C, and the remaining energy amount of the vehicle at that time A road section where the vehicle can travel is determined and a travelable distance is obtained.
In addition, when the guide route is not determined, the energy cost of the road section that can proceed from the own vehicle position is sequentially calculated using the energy consumption weighting parameter C, and the sum of the energy cost of each road section and the From the comparison result with the remaining energy amount of the vehicle, a range in which the vehicle can travel is obtained.

As described above, according to the first embodiment, the parameter E that defines the energy consumption factor of the vehicle in each section based on the traveling state of the vehicle in each section on the route and the route information of each section; An energy consumption model expressing energy consumption Q of a vehicle traveling on the route from parameters C (C ₁ ,..., C ₇ ) that give weighting of energy consumption corresponding to the parameter E of each section. A parameter estimation method for estimating the parameter C based on the relational expressions (1) to (3), in which the travel history information acquisition unit 2 travels the route and consumes the energy consumption Q of the vehicle, the route And the travel history information including information indicating the travel state of the vehicle on the route, and the parameter estimation unit 3 includes the route information included in the travel history information acquired by the travel history information acquisition unit 2 and Based on the relational expression of the energy consumption model, the parameter E is derived based on both driving conditions, and the vehicle energy consumption Q included in the derived parameter E and the traveling history information is used to determine each section on the route. The parameter C at is estimated.
In this way, an energy consumption model that represents the energy consumption Q using the parameter E that can be derived from simple travel history information and the parameter C that gives the weighting of the corresponding energy consumption is used. Therefore, the parameter C corresponding to the energy consumption factor of the vehicle can be estimated while reducing the calculation cost. In addition, since the parameter C can be finally estimated from simple travel history information, information necessary for estimating the parameter can be easily collected for each driver, which affects energy consumption such as a difference between drivers. It can respond flexibly to changes in the situation.

Further, according to the first embodiment, the parameter E depends on the parameter that defines the energy consumption factor depending on the travel time of the vehicle in each section on the route and the travel distance of the vehicle in each section on the route. Parameters that specify the energy consumption factor, parameters that specify the energy consumption factor that depends on the altitude difference in each section on the route, and parameters that specify the energy consumption factor that depends on the air resistance received by the vehicle in each section on the route , And parameters defining energy consumption factors depending on the acceleration / deceleration of the vehicle in each section on the route, and the parameter C is an energy consumption amount corresponding to each energy consumption factor with respect to the parameters included in the parameter E parameter C ₁ giving weight of each, ..., includes a C _7.
By adopting such an energy consumption model, the parameter E can be derived from information indicating the simple driving state such as the speed of the vehicle and the link distance in each section on the route and the route information. Cost can be reduced.

  Furthermore, according to the first embodiment, the navigation device 1 travel history information including the energy consumption of the host vehicle consumed by traveling along the route, the route information of the route, and the traveling state of the vehicle on the route. The travel history information acquisition unit 2 that acquires the parameter, the parameter estimation unit 3 that estimates the parameter C by the parameter estimation method described above using the travel history information acquired by the travel history information acquisition unit 2, and the parameter estimation unit 3 And a route search processing unit 5 for performing a route search considering energy consumption based on the parameter C. Thereby, the navigation apparatus which searches and guides the route in consideration of the energy consumption can be provided.

Embodiment 2. FIG.
In the first embodiment, the case where the energy consumption weighting parameter C is used for the route search is shown. However, in the second embodiment, the driver's driving characteristics or the vehicle using the energy consumption weighting parameter C is shown. A configuration for evaluating the characteristics will be described.
FIG. 5 is a block diagram showing a configuration of a navigation device according to Embodiment 2 of the present invention, and shows a navigation device mounted on a vehicle as a moving body, similarly to Embodiment 1 described above. In FIG. 5, the navigation device 1A estimates the weighting parameter C of the energy consumption for each road section based on the energy consumption model of the above formulas (1) to (3) using the traveling history information of the own vehicle. Using this, it has a function of evaluating driving characteristics related to the energy consumption of the driver or vehicle characteristics related to the energy consumption of the vehicle.

  In the navigation apparatus 1A, a characteristic evaluation unit 8 and an evaluation information presentation unit 9 are added to the configuration of the first embodiment. The characteristic evaluation unit 8 uses the parameter C estimated by the parameter estimation unit 3 to evaluate driving characteristics related to the driver's energy consumption or vehicle characteristics related to the vehicle's energy consumption. The evaluation information presentation unit 9 is a presentation unit that presents the evaluation result from the characteristic evaluation unit 8 and outputs a display device, voice guidance, and the like that displays a map and a guidance route to the user and displays an HMI screen for various operations. It is comprised from the speaker which is an audio | voice output apparatus. In FIG. 5, the same components as those in FIG.

Next, the operation will be described.
{1} Evaluation of Driving Characteristics First, the case where the driving characteristics of the driver are evaluated using the weighting parameter C of the energy consumption estimated by the parameter estimation unit 3 will be described.
FIG. 6 is a flowchart illustrating an example of the driving characteristic evaluation process performed by the characteristic evaluation unit according to the second embodiment.
The characteristic evaluation unit 8 obtains the energy consumption weighting parameters C (C ₁ ,..., C ₇ ) estimated by the parameter estimation unit 3 based on the travel history information of the driver to be evaluated ( Step ST1b).
Next, characteristic evaluation unit 8, a preset reference parameters C of (C _1, · · ·, C ₇₎ and the parameter C obtained in step _{ST1b (C 1, ···, C} 7) and In comparison, it is determined whether or not the values of the parameters C ₆ and C ₇ in the relational expression depending on the acceleration / deceleration of the vehicle are relatively larger than the parameters C _{1 to} C _5. The degree of eco-driving is evaluated as a characteristic (step ST2b). For example, the ratio of C ₆ and C ₇ to the total parameter value (C ₆ / (C ₁ +... + C ₇ ), C ₇ / (C ₁ +... + C ₇ ) or (C ₆ + C ₇ ) / (C ₁ +... + C ₇ )) may be used for relative determination. That is, if the ratio is larger than the ratio in the preset reference parameter, it is regarded as relatively large.
As the reference parameter C (C ₁ ,..., C ₇ ), for example, a value estimated in advance using travel history information obtained by experimentally traveling the same travel route with the same vehicle is used. To do. Or it is good also considering the parameter C estimated using the driving | running history information of multiple times obtained with the same vehicle and the driving | running route as a reference | standard.

When the values of the parameters C ₆ and C ₇ are not relatively large compared to the parameters C _{1 to} C ₅ , the characteristic evaluation unit 8 is an operation in which the acceleration / deceleration of the vehicle that particularly affects the energy consumption is small. However, the driver to be evaluated evaluates that the degree of eco-driving is high (driving characteristics with low energy consumption) (step ST3b).
In addition, when the values of the parameters C ₆ and C ₇ are relatively large compared to the parameters C _{1 to} C ₅ , since the vehicle is accelerating and decelerating, the characteristic evaluation unit 8 determines the driver to be evaluated. Evaluates that the degree of eco-driving is low (driving characteristics with high energy consumption) (step ST4b).
The evaluation result is output from the characteristic evaluation unit 8 to the evaluation information presentation unit 9. The evaluation information presentation unit 9 presents the evaluation result by the characteristic evaluation unit 8 in a visual or audible manner via a display device or an audio output device (step ST5b).

The characteristic evaluation unit 8 performs eco-driving based on whether or not the values of the parameters C ₆ and C ₇ in the relational expression depending on the acceleration / deceleration of the host vehicle are relatively larger than the parameters C _{1 to} C _5. You may evaluate whether it is a state or a non-eco-driving state.
Moreover, the characteristic evaluation unit 8, to classify the relative magnitude in comparison with the parameters C ₁ -C ₅ parameter C _6, C ₇ in more detail, may define the degree of eco-driving. In this case, for example, the evaluation information presenting unit 9 may display an indicator indicating the degree of eco-driving on the screen or perform voice guidance indicating the degree of eco-driving.

On the other hand, the characteristic evaluation unit 8 is a weighting parameter C (C ₁ ,..., C ₇ ) of the energy consumption estimated by the parameter estimation unit 3 based on the travel history information of a plurality of times by the same driver. From this tendency, the improvement or deterioration tendency of the degree of eco-driving is evaluated and presented to the driver (step ST6b). For example, the reference parameter C set in advance and the parameter C estimated based on the above-described multiple travel history information are sequentially compared and compared with the parameters C _{1 to} C ₅ of the parameters C ₆ and C _7. The trend of improvement or deterioration of the degree of eco-driving is evaluated and presented from the trend of relative size.

{2} Evaluation of vehicle characteristics Next, the case where the vehicle characteristics are evaluated using the parameter C estimated by the parameter estimation unit 3 will be described.
FIG. 7 is a flowchart illustrating an example of a vehicle characteristic evaluation process performed by the characteristic evaluation unit according to the second embodiment. In FIG. 7, the evaluation information presentation unit 9 omits the process of presenting the evaluation result by the characteristic evaluation unit 8. However, as in step ST <b> 5 b of FIG. 6, the evaluation information presentation unit 9 displays the display device or voice. The evaluation result may be presented in a visual or audible manner via the output device.

First, the characteristic evaluation unit 8 calculates the energy consumption amount estimated by the parameter estimation unit 3 based on the travel history information of different vehicles on the same driver and the same travel route, similarly to step ST1b in FIG. Weighting parameters C (C ₁ ,..., C ₇ ) are acquired.
The characterization unit 8, the parameters C of a preset reference (C _1, · · ·, C ₇₎ and the parameter C obtained as described above (C _1, · · ·, C ₇₎ and In comparison, it is determined whether or not each parameter value is relatively larger than the reference parameter C, and the eco degree is evaluated as a characteristic of the vehicle to be evaluated (step ST1c). In addition, you may determine a relative magnitude | size similarly to the case of FIG. For example, the parameter C _3, the case of C _4, the ratio _{(C 3 / (C 1 +} ··· + C 7 occupied by the C _3, C ₄ to the sum of the parameter _{values), C 4 / (C 1} + ··· + C ₇ ) or (C ₃ + C ₄ ) / (C ₁ +... + C ₇ )) may be used to determine the relative values of C ₃ and C ₄ . That is, if the ratio is larger than the ratio in the preset reference parameter, it is regarded as relatively large.

When the parameter C ₁ is relatively smaller than the parameters C _{2 to} C ₇ , the characteristic evaluation unit 8 uses the energy consumption that is the base of the vehicle to be evaluated, that is, the basic energy consumption per unit time (cc / s). Alternatively, it is evaluated that W) is small (step ST2c-1).
When the parameter C ₂ is relatively smaller than the parameters C ₁ and C _{3 to} C ₇ , the characteristic evaluation unit 8 evaluates that the rolling resistance of the vehicle to be evaluated is small (step ST2c-2).
When the parameters C ₃ and C ₄ are relatively small compared to the parameters C ₁ , C ₂ , and C _{5 to} C ₇ , the characteristic evaluation unit 8 climbs up and down at a place where the vehicle to be evaluated has an altitude difference. (STEP ST2c-3).
Characterization unit 8, the parameter C ₅ is if relatively small compared with the parameters _{C 1 ~C 4, C 6,} C 7 , the air resistance of the vehicle to be evaluated is evaluated as low (step ST2c-4 ).

As described above, according to the second embodiment, based on the parameter C estimated by the parameter estimation method shown in the first embodiment, the driving characteristics related to the energy consumption of the vehicle or the energy consumption of the mobile body a characteristic evaluation method for evaluating the characteristics associated with the characteristic evaluation unit 8 obtains the parameter C, the parameters C ₁ included in the parameter C, · · ·, from the relative sizes of C _7, the The influence of the energy consumption factor that the parameter gives the energy consumption weighting is determined to evaluate the driving characteristics related to the energy consumption of the vehicle or the characteristics related to the energy consumption of the vehicle. By doing so, it is possible to estimate the parameter C corresponding to the energy consumption factor of the moving object while reducing the calculation cost, and using the estimated parameter C, the energy consumption of the driving characteristics related to the energy consumption of the driver Vehicle characteristics related to the vehicle can be evaluated.

Further, according to the second embodiment, the characteristic evaluation unit 8 includes a parameter that defines an energy consumption factor depending on the travel time of the vehicle in each section on the route, which is included in the parameter E among the parameters C. Parameters that specify energy consumption factors depending on the travel distance of the vehicle in each section on the route, parameters that specify energy consumption factors that depend on the altitude difference in each section on the route, and vehicles in each section on the route The relative size of the parameter that gives the weight of the energy consumption corresponding to at least one of the parameters that define the energy consumption factor depending on the air resistance to be received is the parameter C (C ₁ ,..., C _7. The characteristics related to the energy consumption of the vehicle are evaluated according to whether or not they are larger than the other parameters. Thereby, the vehicle characteristic related to energy consumption can be evaluated using the estimated parameter C.

In the first and second embodiments, the case where the mobile navigation device 1 according to the present invention is applied to a vehicle-mounted navigation device has been described. However, not only the vehicle-mounted device but also a mobile phone terminal or a personal digital assistant (PDA; You may apply to Personal Digital Assistance.
Moreover, you may apply to PND (Portable Navigation Device) etc. which a person carries and uses in moving bodies, such as a vehicle, a railroad, a ship, or an aircraft.

  In the present invention, within the scope of the invention, any combination of each embodiment, any component of each embodiment can be modified, or any component can be omitted in each embodiment. .

  Since the parameter estimation method according to the present invention can accurately estimate the energy consumption on the route while reducing the calculation cost, it is suitable for a vehicle-mounted navigation device that performs navigation processing in consideration of the energy cost.

  DESCRIPTION OF SYMBOLS 1 Navigation apparatus, 2 Travel history information acquisition part, 2a Travel history information storage part, 2b Vehicle information acquisition part, 3 Parameter estimation part, 4 Link cost calculation part, 5 Route search process part, 6 User input part, 7 Map database ( DB), 8 characteristic evaluation part, 9 evaluation information presentation part.

  The present invention relates to a parameter estimation method for estimating a parameter that gives a weight of an energy consumption amount corresponding to an energy consumption factor of a moving body such as a vehicle, and the operation of the moving body or the moving body itself using the parameter estimated by this method. The present invention relates to a characteristic evaluation method for evaluating characteristics, and a navigation device for searching for a route in consideration of energy consumption calculated using parameters estimated by this method.

  In order to search for a route with the minimum energy consumption, it is necessary to predict the energy consumption during traveling for a road segment on the route. For example, in Patent Document 1, an estimation method for estimating a propulsive force-related operation parameter unique to a vehicle or a driver thereof using vehicle travel data and a route search using the estimated propulsion-related operation parameter are performed. A navigation system is disclosed.

  In the estimation method disclosed in Patent Document 1, a driving phase such as rest, start, and low-speed driving is estimated, and vehicle-specific parameters such as a rolling drag coefficient of the vehicle related to each driving phase are estimated. Then, using the estimated vehicle-specific parameters, driving force-related operation parameters such as fuel consumption, energy consumption, and carbon dioxide emission are estimated.

JP 2010-190895 A

  In the estimation method described in Patent Document 1, a vehicle-specific parameter is estimated using a vehicle model corresponding to a traveling phase. Therefore, it is necessary to collect travel data according to each travel phase, and further, a different model for the vehicle subsystem according to the travel phase is required. For this reason, there existed a subject that the calculation cost required for parameter estimation increased.

  Further, in Patent Document 1, since travel data for each travel phase is required, the amount of travel data to be collected inevitably increases. For example, when estimating driving force-related operation parameters of different drivers, it is necessary to collect travel data corresponding to each driver for each travel phase. Therefore, it is not possible to flexibly cope with a change in the situation that affects the energy consumption of the vehicle such as a difference in drivers.

  Furthermore, since the estimation method described in Patent Document 1 indirectly estimates the propulsive force-related operation parameter using a model corresponding to information related to vehicle propulsion such as torque and engine rotation speed, Detailed travel data such as torque, gear, and brake pressure are required.

  The present invention has been made to solve the above-described problems, and can estimate a parameter that gives a weight of energy consumption corresponding to an energy consumption factor of a moving object while reducing the calculation cost. A parameter estimation method capable of flexibly responding to changes in the situation affecting consumption, a characteristic evaluation method for evaluating the operation of the moving body or the characteristics of the moving body using the parameters estimated by this method, and the estimation using this method It is an object of the present invention to obtain a navigation device that performs navigation processing in consideration of energy consumption calculated using the parameters.

The parameter estimation method according to the present invention includes a first parameter that defines the energy consumption factor of the moving body in each section based on the moving state of the moving body in each section on the route and the path information of each section, Based on the relational expression of the energy consumption model that expresses the energy consumption of the mobile body that has moved along the route from the second parameter that gives the weight of the energy consumption corresponding to the first parameter of the section, the second parameter Is a parameter estimation method for estimating the parameters of the vehicle, wherein the history information acquisition unit indicates the energy consumption amount of the mobile body consumed by moving the route, the route information of the route, and the moving state of the mobile body on the route The movement history information including the information is acquired, and the parameter estimation unit determines the first parameter based on the route information included in the movement history information acquired by the history information acquisition unit and the movement state of the moving body. Derive the meter, using the energy consumption of the moving object contained in the derived first parameters and movement history information, based on the relationship of the energy consumption model, the moving body in each section on the route A second parameter is calculated such that an estimation error with respect to the energy consumption is reduced .

  According to the present invention, it is possible to estimate the parameter that gives the weight of the energy consumption corresponding to the energy consumption factor of the mobile body while reducing the calculation cost, and to flexibly cope with the change in the situation that affects the energy consumption. There is an effect that can be.

It is a block diagram which shows the structure of the navigation apparatus which concerns on Embodiment 1 of this invention. 3 is a flowchart showing a flow of parameter estimation processing by a parameter estimation unit according to Embodiment 1. 6 is a conceptual diagram of parameter estimation according to Embodiment 1. FIG. 4 is a flowchart illustrating a flow of route search processing by the navigation device according to the first embodiment. It is a block diagram which shows the structure of the navigation apparatus concerning Embodiment 2 of this invention. 10 is a flowchart illustrating an example of a driving characteristic evaluation process by a characteristic evaluation unit according to the second embodiment. 6 is a flowchart illustrating an example of a vehicle characteristic evaluation process performed by a characteristic evaluation unit according to Embodiment 2.

Hereinafter, in order to describe the present invention in more detail, modes for carrying out the present invention will be described with reference to the accompanying drawings.
Embodiment 1 FIG.
FIG. 1 is a block diagram showing the configuration of a navigation device mounted on a mobile body (for example, a vehicle) according to Embodiment 1 of the present invention. In FIG. 1, a navigation device 1 uses a travel history information of a vehicle (hereinafter referred to as “own vehicle”) on which the navigation device 1 is mounted, based on an energy consumption model described later, a road section (a road link defined by map data). ) To estimate the parameter that gives the weight of energy consumption corresponding to each energy consumption factor, and to apply the estimated parameter to the navigation process. The parameter that gives the weight of the energy consumption corresponding to the energy consumption factor is a parameter of the energy consumption model handled in the present invention, and details thereof will be described later.

The navigation device 1 includes, as its configuration, a travel history information acquisition unit 2, a travel history information storage unit 2a, a vehicle information acquisition unit 2b, a parameter estimation unit 3, a link cost calculation unit 4, a route search processing unit 5, and a user input unit 6. And a map database (DB) 7.
The travel history information acquisition unit 2 is a history information acquisition unit that acquires travel history information used for estimating the parameters from the travel history information storage unit 2a. The travel history information includes information on the travel route of the vehicle, for example, travel time, travel speed, stop, acceleration / deceleration of the vehicle, and energy consumption in travel of the travel route.
The travel history information storage unit 2a is a storage unit that stores travel history information, and stores travel history information in association with the driver and the traveling vehicle.
The vehicle information acquisition unit 2b is a configuration unit that acquires vehicle information of the host vehicle, and includes a sensor that measures vehicle information stored as travel history information and a vehicle control unit. The vehicle information includes actual measurement data such as the position of the host vehicle, the traveling speed of the host vehicle traveling on the route, acceleration / deceleration, stop, energy consumption, and the like.

  The parameter estimation unit 3 uses the travel history information related to the processing target travel route acquired by the travel history information acquisition unit 2 and the map data of the travel route in the map DB 7, and uses the road section of the travel route according to the energy consumption model described later. A weighting parameter for each energy consumption is estimated. The link cost calculation unit 4 relates to the energy consumption amount for each road section in the travel route to be processed from the weighting parameter of the energy consumption amount for each road section estimated by the parameter estimation unit 3 and the corresponding road data in the map DB 7. It is a component which calculates a link cost.

  The route search processing unit 5 is a route search unit that searches for a route that minimizes the energy cost connecting the start point and the end point based on the link cost related to the energy consumption for each road section calculated by the link cost calculation unit 4. . The user input unit 6 is a component that receives a setting input of a start point (for example, a departure point) and an end point (for example, a destination) by a user, and is realized by, for example, a touch panel mounted on the screen of a display device. The map DB 7 is a database that stores map data used in navigation processing such as route search. The map data includes, for example, road data indicating a node, a road link connecting the nodes, a road type that is a road attribute of the road link, an elevation difference of the road link, and the like.

Here, the energy consumption model handled in the present invention will be described.
The travel time in the jth road section on the travel route i is T _ij, and the link distance that is the length of the road section is D _ij . These are specified from the traffic characteristics on the travel route i, that is, the traveling state of the own vehicle.
Further, the sum of the climbing elevation differences that is the sum of the elevation differences of the climbing road sections in the road section is H _{up_ij,} and the sum of the descending elevation differences that is the sum of the elevation differences of the descending road sections in the road section is H _{down_ij} . These are specified from road data of the travel route i, for example, road attributes.
It is _assumed that the traveling speed of the vehicle in the jth road section on the traveling route i is v _ij , the number of accelerations from the stop of the vehicle in the road section is N _{stop_ij} , and the number of accelerations from the deceleration is N _{decc_ij} . These parameters are specified from the traffic characteristics (traveling state of the host vehicle) on the travel route i.
Furthermore, if the parameters that give the weighting of the energy consumption that is the object of estimation (correction) are C ₁ ,..., C ₇ , the vehicle travels on the jth road section on the travel route i. energy consumption Q _i and the parameters C _1, · · ·, between the C _7, holds the relationship of the following formula (1).
Where q _base is the basic energy consumption per unit time (cc / s or W).
μ is a friction coefficient (−) between the tire of the own vehicle and the road surface, and κ is an air resistance coefficient (−) of the own vehicle.
M is the vehicle weight of the own vehicle, and a value such as 1500 (kg) is set, for example.
m is inertia, for example, a value such as 0.2 · M (kg) is set.
g is a gravitational acceleration, and is set to 10.0 (m / s ² ), for example.
ε is the net thermal efficiency (−), and η is the total transmission efficiency (−).
H is a fuel calorie conversion coefficient, and is set to a value such as 3.4 · 10000 (J / cc), for example.
v _{stop_s} is the speed (= 0 (km / h)) at the start of acceleration from the stop of the _host vehicle.
v _{stop_e} is the speed at the end of acceleration from the stop of the _host vehicle, that is, the travel speed at which the acceleration is stopped from the stop state and the acceleration is terminated. When the travel route i is a highway, for example, 100 (km / h) ) Is set.
v _{decc_s} is the speed at the time of starting acceleration from the deceleration of the _host vehicle, that is, the traveling speed at which the acceleration starts again after decelerating. For example, up to 90 (km / h) when the traveling route i is a highway Set to start accelerating when decelerated.
v _{decc_e} is the speed at the end of acceleration from the deceleration of the _host vehicle. For example, 110 (km / h) is set as the traveling speed at which acceleration is terminated after acceleration from 90 (km / h).

When the portions other than the weighting parameters C ₁ ,..., C _{7 in} each term on the right side of the above equation (1) are expressed as E _i1 ,..., E _i7 , the following equation (2) is obtained. E _i1 ,..., E _i7 are included in the travel time, travel distance, travel speed, number of accelerations, and road data of the travel route i (map data of the map DB 7) included in the travel history information of the travel route i. This is a parameter that can be calculated using the difference in elevation of the road link.
That is, the first term on the right side of the above equation (1) is a parameter that defines an energy consumption factor depending on the travel time in the jth road section on the travel route i.
The second term on the right side of the above equation (1) is a parameter that defines an energy consumption factor depending on the travel distance of the jth road section on the travel route i.
The third term and the fourth term on the right side of the above formula (1) are parameters that define energy consumption factors depending on the altitude difference in the jth road section on the travel route i. The third term is the climb road section. The energy consumption factor depending on the sum of the altitude difference is defined, and the fourth term defines the energy consumption factor depending on the sum of the altitude difference of the descending road section.
The fifth term on the right side of the equation (1) is a parameter that defines an energy consumption factor depending on the air resistance received by the vehicle in the jth road section on the travel route i.
Further, the sixth term and the seventh term on the right side of the above formula (1) are parameters defining energy consumption factors depending on the acceleration / deceleration of the vehicle in the jth road section on the travel route i. Defines the energy consumption factor depending on the number of accelerations since the stop, and the seventh term defines the energy consumption factor dependent on the number of accelerations after the deceleration.
Q _i = C ₁ · E _i1 + C ₂ · E _i2 + C ₃ · E _i3 + C ₄ · E _i4 + C ₅ · E _i5 + C ₆ · E _i6 + C ₇ · E _i7 (2)

上記式（１）〜（３）が、本発明で扱うエネルギ消費量モデルの関係式である。 Furthermore, when the travel history regarding ma travel routes (i = ma) is obtained, the relationship of the following formula (3) is established. By solving this equation (Q = EC) with respect to the energy consumption weighting parameter C, a parameter C (C ₁ , C) giving a weighting of the energy consumption corresponding to the energy consumption Q _i measured by actual traveling of the vehicle. .., C ₇ ) can be estimated.

The above formulas (1) to (3) are relational expressions of the energy consumption model handled in the present invention.

Next, the operation will be described.
{1} Estimation of Parameter C FIG. 2 is a flowchart showing the flow of parameter estimation processing by the parameter estimation unit according to Embodiment 1. FIG. 3 is a conceptual diagram of parameter estimation according to the first embodiment. Here, a method for correcting the parameter C of the energy consumption model using the travel history information acquired a plurality of times for the target travel route will be described.
First, the parameter estimation unit 3 uses the actual energy consumption Q _i measured in the actual travel of the vehicle on the travel route i from the travel history information of the travel route i to be processed acquired by the travel history information acquisition unit 2. Is extracted (step ST1).

Next, the parameter estimation unit 3 uses the travel history information of the travel route i and the corresponding map data in the map DB 7 (road data of the travel route i) to calculate the travel time T in the jth road section on the travel route i. _ij , the link distance D _ij which is the length of the road section, the sum of the elevation difference H _{up_ij} which is the sum of the _height differences of the climb road sections in the road section, the sum which is the sum of the _height differences of the descending road sections in the road section the sum of the altitude difference H _{Down_ij,} acceleration number N _{Stop_ij} from the traveling speed v _ij and stopping of the vehicle in the road section, obtains the acceleration number N _{Decc_ij} from deceleration.
The parameter estimation unit 3 calculates the T _ij, D _ij, energy _{H up_ij, H down_ij, v ij} , N stop_ij, using the value of N _{Decc_ij,} represented by the above formula (1) to (3) A parameter E of the consumption model is calculated (step ST2). As described above, the parameter E reflects the road attributes and traffic characteristics of the travel route i.

Next, the parameter estimation unit 3 uses the actual energy consumption Q _i and the parameter E (E _i1 ,..., E _i7 ) to calculate the energy consumption weighting parameter C from the above equations (1) to (3). (C ₁ ,..., C ₇ ) are calculated (step ST3).
For example, as shown in FIG. 3, when a travel history regarding ma travel routes (i = ma) is obtained, the above formulas (1) to (3) are used by using the actual energy consumption Q _i and the parameter E. ) With respect to the energy consumption weighting parameters C (C ₁ ,..., C ₇ ).
Thereby, the energy consumption weighting parameter C (C ₁ ,..., C ₇ ) can be estimated. That is, it is possible to calculate the weighting parameters C (C ₁ ,..., C ₇ ) that reduce the estimation error with respect to the actual energy consumption Q _i .
This corresponds to solving simultaneous linear equations, and a solution that minimizes the error is obtained using a pseudo inverse matrix.

Although the case where the parameter C is obtained as a solution that minimizes the estimation error with respect to the actual energy consumption Q _i using the pseudo inverse matrix in the above equation (3) is shown, the parameter C is obtained by a simpler method. Also good. For example, the suboptimal parameter C may be obtained by limiting the value of the parameter C by fixing the possible range and the discretization unit and performing a full search on the points where the parameter space is limited by discretization. .
In addition, when the number of parameters C increases and the calculation time required for the solution becomes longer, a solution such as a quadratic programming method may be adopted to increase the speed.

As described above, in the parameter estimation method of the present invention, in the energy consumption model represented by the above formulas (1) to (3), the energy consumption Q on the travel route, the travel time on each route, and the travel The parameter E related to the distance may be obtained from the travel history information.
In this case, as shown in FIG. 2, the travel time T _ij , the number of accelerations N _{stop_ij} , and N _{decc_ij} may be obtained using detailed travel history information including the travel speed of the vehicle.
If detailed travel history information cannot be obtained, the travel time T _ij and the number of accelerations are calculated using the road type or the number of traffic lights of the road section (road link) on the travel route i included in the map data. N _{stop_ij} and N _{decc_ij} may be estimated.
In that case, detailed information such as travel speed is not necessary, and the parameter C can be estimated by storing the total energy consumption Q and travel route i for each travel.

{2} Route Search Processing Applying Parameter C FIG. 4 is a flowchart showing the flow of route search processing by the navigation device according to the first embodiment. In particular, route search is performed for parameter C estimated as {1}. The case where it applies to is shown.
First, the travel history information acquisition unit 2 acquires the travel history information of the host vehicle from the travel history information storage unit 2a (step ST1a).
Next, the parameter estimation unit 3 uses the travel history information acquired by the travel history information acquisition unit 2 and parameters C (C ₁ ,..., C ₇ ) based on the above formulas (1) to (3). Is estimated (step ST2a).

  Thereafter, the route search processing unit 5 provides an HMI (Human Machine Interface) for setting a start point and an end point for receiving a setting input using the user input unit 6. Based on this HMI, the user determines the start point and end point of the route (step ST3a). Subsequently, information indicating the start point and end point of the route is set in the route search processing unit 5 based on an instruction from the user to the user input unit 6.

Next, the route search processing unit 5 uses the map data of the map DB 7 to calculate one or a plurality of route candidates connecting the start point and the end point, and for each road section (road link) on the route candidate. In addition, the energy cost is calculated using the value of the weighting parameter C (C ₁ ,..., C ₇ ) of the energy consumption amount of the corresponding road section estimated by the parameter estimation unit 3.
In this way, the route search processing unit 5 searches for a route having a minimum total energy cost among the route candidates connecting the start point and the end point (step ST4a). Thereafter, route guidance is executed with the route of the search result as the recommended route.

In addition, various scenes are assumed for the timing of estimating the energy consumption weighting parameter C. For example, the travel history information of vehicles of representative vehicle types before the shipment of the navigation device 1 according to the present invention is collected, the weighting parameter C of the energy consumption amount of each road section is estimated, and the map data (road data) is supported. At the same time, it is stored in the navigation device 1. The weighting parameter C estimated in advance is used for route search after shipment.
In this case, the weighting parameter C estimated in advance is used as an initial value (default), and the value of the parameter C is set to the own vehicle in the same manner as {1} based on the traveling history information obtained by traveling the own vehicle. You may correct | amend together.
For example, when real-time energy consumption information can be used through the vehicle's CAN (Controller Area Network) or the like, the energy consumption weighting parameter is set in accordance with the characteristics of the vehicle or the driver when the navigation device 1A is used. C (C ₁ ,..., C ₇ ) may be adjusted online.

  Further, the travel history information is selected according to the driver or the travel date and stored in the travel history information storage unit 2a, and the parameter estimation unit 3 uses the travel history information corresponding to the driver or the travel date and time. The weighting parameter C unique to the driver or unique to the date and time such as day of the week or season may be estimated. By doing in this way, the estimation precision of energy cost can be improved and it is possible for the route search process part 5 to search for an optimal route according to a driver | operator or driving | running | working date.

In the above description, the case where the estimated energy consumption weighting parameter C is used for the route search is shown. However, the calculation of the travelable distance with respect to the remaining energy amount when the guide route is determined, or the guide route The energy consumption weighting parameter C may be used for calculating the travelable range with respect to the remaining energy amount when the energy consumption is not determined.
For example, when the guide route is determined, the energy cost of each road section from the current position to the destination is calculated using the energy consumption weighting parameter C, and the remaining energy amount of the vehicle at that time A road section where the vehicle can travel is determined and a travelable distance is obtained.
In addition, when the guide route is not determined, the energy cost of the road section that can proceed from the own vehicle position is sequentially calculated using the energy consumption weighting parameter C, and the sum of the energy cost of each road section and the From the comparison result with the remaining energy amount of the vehicle, a range in which the vehicle can travel is obtained.

As described above, according to the first embodiment, the parameter E that defines the energy consumption factor of the vehicle in each section based on the traveling state of the vehicle in each section on the route and the route information of each section; An energy consumption model expressing energy consumption Q of a vehicle traveling on the route from parameters C (C ₁ ,..., C ₇ ) that give weighting of energy consumption corresponding to the parameter E of each section. A parameter estimation method for estimating the parameter C based on the relational expressions (1) to (3), in which the travel history information acquisition unit 2 travels the route and consumes the energy consumption Q of the vehicle, the route And the travel history information including information indicating the travel state of the vehicle on the route, and the parameter estimation unit 3 includes the route information included in the travel history information acquired by the travel history information acquisition unit 2 and Based on the relational expression of the energy consumption model, the parameter E is derived based on both driving conditions, and the vehicle energy consumption Q included in the derived parameter E and the traveling history information is used to determine each section on the route. The parameter C at is estimated.
In this way, an energy consumption model that represents the energy consumption Q using the parameter E that can be derived from simple travel history information and the parameter C that gives the weighting of the corresponding energy consumption is used. Therefore, the parameter C corresponding to the energy consumption factor of the vehicle can be estimated while reducing the calculation cost. In addition, since the parameter C can be finally estimated from simple travel history information, information necessary for estimating the parameter can be easily collected for each driver, which affects energy consumption such as a difference between drivers. It can respond flexibly to changes in the situation.

Further, according to the first embodiment, the parameter E depends on the parameter that defines the energy consumption factor depending on the travel time of the vehicle in each section on the route and the travel distance of the vehicle in each section on the route. Parameters that specify the energy consumption factor, parameters that specify the energy consumption factor that depends on the altitude difference in each section on the route, and parameters that specify the energy consumption factor that depends on the air resistance received by the vehicle in each section on the route , And parameters defining energy consumption factors depending on the acceleration / deceleration of the vehicle in each section on the route, and the parameter C is an energy consumption amount corresponding to each energy consumption factor with respect to the parameters included in the parameter E parameter C ₁ giving weight of each, ..., includes a C _7.
By adopting such an energy consumption model, the parameter E can be derived from information indicating the simple driving state such as the speed of the vehicle and the link distance in each section on the route and the route information. Cost can be reduced.

  Furthermore, according to the first embodiment, the navigation device 1 travel history information including the energy consumption of the host vehicle consumed by traveling along the route, the route information of the route, and the traveling state of the vehicle on the route. The travel history information acquisition unit 2 that acquires the parameter, the parameter estimation unit 3 that estimates the parameter C by the parameter estimation method described above using the travel history information acquired by the travel history information acquisition unit 2, and the parameter estimation unit 3 And a route search processing unit 5 for performing a route search considering energy consumption based on the parameter C. Thereby, the navigation apparatus which searches and guides the route in consideration of the energy consumption can be provided.

Embodiment 2. FIG.
In the first embodiment, the case where the energy consumption weighting parameter C is used for the route search is shown. However, in the second embodiment, the driver's driving characteristics or the vehicle using the energy consumption weighting parameter C is shown. A configuration for evaluating the characteristics will be described.
FIG. 5 is a block diagram showing a configuration of a navigation device according to Embodiment 2 of the present invention, and shows a navigation device mounted on a vehicle as a moving body, similarly to Embodiment 1 described above. In FIG. 5, the navigation device 1A estimates the weighting parameter C of the energy consumption for each road section based on the energy consumption model of the above formulas (1) to (3) using the traveling history information of the own vehicle. Using this, it has a function of evaluating driving characteristics related to the energy consumption of the driver or vehicle characteristics related to the energy consumption of the vehicle.

  In the navigation apparatus 1A, a characteristic evaluation unit 8 and an evaluation information presentation unit 9 are added to the configuration of the first embodiment. The characteristic evaluation unit 8 uses the parameter C estimated by the parameter estimation unit 3 to evaluate driving characteristics related to the driver's energy consumption or vehicle characteristics related to the vehicle's energy consumption. The evaluation information presentation unit 9 is a presentation unit that presents the evaluation result from the characteristic evaluation unit 8 and outputs a display device, voice guidance, and the like that displays a map and a guidance route to the user and displays an HMI screen for various operations. It is comprised from the speaker which is an audio | voice output apparatus. In FIG. 5, the same components as those in FIG.

Next, the operation will be described.
{1} Evaluation of Driving Characteristics First, the case where the driving characteristics of the driver are evaluated using the weighting parameter C of the energy consumption estimated by the parameter estimation unit 3 will be described.
FIG. 6 is a flowchart illustrating an example of the driving characteristic evaluation process performed by the characteristic evaluation unit according to the second embodiment.
The characteristic evaluation unit 8 obtains the energy consumption weighting parameters C (C ₁ ,..., C ₇ ) estimated by the parameter estimation unit 3 based on the travel history information of the driver to be evaluated ( Step ST1b).
Next, characteristic evaluation unit 8, a preset reference parameters C of (C _1, · · ·, C ₇₎ and the parameter C obtained in step _{ST1b (C 1, ···, C} 7) and In comparison, it is determined whether or not the values of the parameters C ₆ and C ₇ in the relational expression depending on the acceleration / deceleration of the vehicle are relatively larger than the parameters C _{1 to} C _5. The degree of eco-driving is evaluated as a characteristic (step ST2b). For example, the ratio of C ₆ and C ₇ to the total parameter value (C ₆ / (C ₁ +... + C ₇ ), C ₇ / (C ₁ +... + C ₇ ) or (C ₆ + C ₇ ) / (C ₁ +... + C ₇ )) may be used for relative determination. That is, if the ratio is larger than the ratio in the preset reference parameter, it is regarded as relatively large.
As the reference parameter C (C ₁ ,..., C ₇ ), for example, a value estimated in advance using travel history information obtained by experimentally traveling the same travel route with the same vehicle is used. To do. Or it is good also considering the parameter C estimated using the driving | running history information of multiple times obtained with the same vehicle and the driving | running route as a reference | standard.

When the values of the parameters C ₆ and C ₇ are not relatively large compared to the parameters C _{1 to} C ₅ , the characteristic evaluation unit 8 is an operation in which the acceleration / deceleration of the vehicle that particularly affects the energy consumption is small. However, the driver to be evaluated evaluates that the degree of eco-driving is high (driving characteristics with low energy consumption) (step ST3b).
In addition, when the values of the parameters C ₆ and C ₇ are relatively large compared to the parameters C _{1 to} C ₅ , since the vehicle is accelerating and decelerating, the characteristic evaluation unit 8 determines the driver to be evaluated. Evaluates that the degree of eco-driving is low (driving characteristics with high energy consumption) (step ST4b).
The evaluation result is output from the characteristic evaluation unit 8 to the evaluation information presentation unit 9. The evaluation information presentation unit 9 presents the evaluation result by the characteristic evaluation unit 8 in a visual or audible manner via a display device or an audio output device (step ST5b).

The characteristic evaluation unit 8 performs eco-driving based on whether or not the values of the parameters C ₆ and C ₇ in the relational expression depending on the acceleration / deceleration of the host vehicle are relatively larger than the parameters C _{1 to} C _5. You may evaluate whether it is a state or a non-eco-driving state.
Moreover, the characteristic evaluation unit 8, to classify the relative magnitude in comparison with the parameters C ₁ -C ₅ parameter C _6, C ₇ in more detail, may define the degree of eco-driving. In this case, for example, the evaluation information presenting unit 9 may display an indicator indicating the degree of eco-driving on the screen or perform voice guidance indicating the degree of eco-driving.

On the other hand, the characteristic evaluation unit 8 is a weighting parameter C (C ₁ ,..., C ₇ ) of the energy consumption estimated by the parameter estimation unit 3 based on the travel history information of a plurality of times by the same driver. From this tendency, the improvement or deterioration tendency of the degree of eco-driving is evaluated and presented to the driver (step ST6b). For example, the reference parameter C set in advance and the parameter C estimated based on the above-described multiple travel history information are sequentially compared and compared with the parameters C _{1 to} C ₅ of the parameters C ₆ and C _7. The trend of improvement or deterioration of the degree of eco-driving is evaluated and presented from the trend of relative size.

{2} Evaluation of vehicle characteristics Next, the case where the vehicle characteristics are evaluated using the parameter C estimated by the parameter estimation unit 3 will be described.
FIG. 7 is a flowchart illustrating an example of a vehicle characteristic evaluation process performed by the characteristic evaluation unit according to the second embodiment. In FIG. 7, the evaluation information presentation unit 9 omits the process of presenting the evaluation result by the characteristic evaluation unit 8. However, as in step ST <b> 5 b of FIG. 6, the evaluation information presentation unit 9 displays the display device or voice. The evaluation result may be presented in a visual or audible manner via the output device.

First, the characteristic evaluation unit 8 calculates the energy consumption amount estimated by the parameter estimation unit 3 based on the travel history information of different vehicles on the same driver and the same travel route, similarly to step ST1b in FIG. Weighting parameters C (C ₁ ,..., C ₇ ) are acquired.
The characterization unit 8, the parameters C of a preset reference (C _1, · · ·, C ₇₎ and the parameter C obtained as described above (C _1, · · ·, C ₇₎ and In comparison, it is determined whether or not each parameter value is relatively larger than the reference parameter C, and the eco degree is evaluated as a characteristic of the vehicle to be evaluated (step ST1c). In addition, you may determine a relative magnitude | size similarly to the case of FIG. For example, the parameter C _3, the case of C _4, the ratio _{(C 3 / (C 1 +} ··· + C 7 occupied by the C _3, C ₄ to the sum of the parameter _{values), C 4 / (C 1} + ··· + C ₇ ) or (C ₃ + C ₄ ) / (C ₁ +... + C ₇ )) may be used to determine the relative values of C ₃ and C ₄ . That is, if the ratio is larger than the ratio in the preset reference parameter, it is regarded as relatively large.

When the parameter C ₁ is relatively smaller than the parameters C _{2 to} C ₇ , the characteristic evaluation unit 8 uses the energy consumption that is the base of the vehicle to be evaluated, that is, the basic energy consumption per unit time (cc / s). Alternatively, it is evaluated that W) is small (step ST2c-1).
When the parameter C ₂ is relatively smaller than the parameters C ₁ and C _{3 to} C ₇ , the characteristic evaluation unit 8 evaluates that the rolling resistance of the vehicle to be evaluated is small (step ST2c-2).
When the parameters C ₃ and C ₄ are relatively small compared to the parameters C ₁ , C ₂ , and C _{5 to} C ₇ , the characteristic evaluation unit 8 climbs up and down at a place where the vehicle to be evaluated has an altitude difference. (STEP ST2c-3).
Characterization unit 8, the parameter C ₅ is if relatively small compared with the parameters _{C 1 ~C 4, C 6,} C 7 , the air resistance of the vehicle to be evaluated is evaluated as low (step ST2c-4 ).

As described above, according to the second embodiment, based on the parameter C estimated by the parameter estimation method shown in the first embodiment, the driving characteristics related to the energy consumption of the vehicle or the energy consumption of the mobile body a characteristic evaluation method for evaluating the characteristics associated with the characteristic evaluation unit 8 obtains the parameter C, the parameters C ₁ included in the parameter C, · · ·, from the relative sizes of C _7, the The influence of the energy consumption factor that the parameter gives the energy consumption weighting is determined to evaluate the driving characteristics related to the energy consumption of the vehicle or the characteristics related to the energy consumption of the vehicle. By doing so, it is possible to estimate the parameter C corresponding to the energy consumption factor of the moving object while reducing the calculation cost, and using the estimated parameter C, the energy consumption of the driving characteristics related to the energy consumption of the driver Vehicle characteristics related to the vehicle can be evaluated.

Further, according to the second embodiment, the characteristic evaluation unit 8 includes a parameter that defines an energy consumption factor depending on the travel time of the vehicle in each section on the route, which is included in the parameter E among the parameters C. Parameters that specify energy consumption factors depending on the travel distance of the vehicle in each section on the route, parameters that specify energy consumption factors that depend on the altitude difference in each section on the route, and vehicles in each section on the route The relative size of the parameter that gives the weight of the energy consumption corresponding to at least one of the parameters that define the energy consumption factor depending on the air resistance to be received is the parameter C (C ₁ ,..., C _7. The characteristics related to the energy consumption of the vehicle are evaluated according to whether or not they are larger than the other parameters. Thereby, the vehicle characteristic related to energy consumption can be evaluated using the estimated parameter C.

In the first and second embodiments, the case where the mobile navigation device 1 according to the present invention is applied to a vehicle-mounted navigation device has been described. However, not only the vehicle-mounted device but also a mobile phone terminal or a personal digital assistant (PDA; You may apply to Personal Digital Assistance.
Moreover, you may apply to PND (Portable Navigation Device) etc. which a person carries and uses in moving bodies, such as a vehicle, a railroad, a ship, or an aircraft.

  In the present invention, within the scope of the invention, any combination of each embodiment, any component of each embodiment can be modified, or any component can be omitted in each embodiment. .

  DESCRIPTION OF SYMBOLS 1 Navigation apparatus, 2 Travel history information acquisition part, 2a Travel history information storage part, 2b Vehicle information acquisition part, 3 Parameter estimation part, 4 Link cost calculation part, 5 Route search process part, 6 User input part, 7 Map database ( DB), 8 characteristic evaluation part, 9 evaluation information presentation part.

The parameter estimation method according to the present invention includes a first parameter that defines the energy consumption factor of the moving body in each section based on the moving state of the moving body in each section on the route and the path information of each section, Based on the relational expression of the energy consumption model that expresses the energy consumption of the mobile body that has moved along the route from the second parameter that gives the weight of the energy consumption corresponding to the first parameter of the section, the second parameter Is a parameter estimation method for estimating the parameters of the vehicle, wherein the history information acquisition unit indicates the energy consumption amount of the mobile body consumed by moving the route, the route information of the route, and the moving state of the mobile body on the route acquires movement history information including information, travel route based on the moving state of the route information and a mobile parameter estimator is included in the movement history information acquired by the history information acquisition unit It derives a first parameter using a number of road type or traffic road segments, with energy consumption of the moving object contained in the derived first parameters and movement history information, energy consumption model Based on the relational expression, the second parameter is calculated such that the estimation error with respect to the energy consumption amount of the moving body in each section on the route becomes small.

Claims (6)

A first parameter that defines an energy consumption factor of the moving body in each section based on a moving state of the moving body in each section on the route and path information of each section; and a first parameter of each section Based on the relational expression of the energy consumption model that expresses the energy consumption of the mobile body that has moved along the route from the second parameter that gives the weight of the energy consumption corresponding to the parameter, the second parameter is A parameter estimation method for estimating,
The history information acquisition unit acquires movement history information including energy consumption amount of a moving body consumed by moving a route, route information of the route, and information indicating a moving state of the moving body on the route,
The parameter estimation unit derives the first parameter based on the route information included in the movement history information acquired by the history information acquisition unit and the moving state of the moving body, and the derived first parameter and the A parameter for estimating the second parameter in each section on the route based on the relational expression of the energy consumption model, using the energy consumption amount of the mobile body included in the movement history information Estimation method. The first parameter defines a parameter that defines an energy consumption factor depending on a moving time of a moving object in each section on the route, and an energy consumption factor that depends on a moving distance of the moving object in each section on the route. Parameters that specify energy consumption factors that depend on the difference in elevation in each section on the route, parameters that define energy consumption factors that depend on the air resistance received by the moving body in each section on the route, and on the route Including parameters that define energy consumption factors depending on the acceleration and deceleration of the moving body in each section,
2. The parameter according to claim 1, wherein the second parameter includes a parameter that gives a weighting of energy consumption corresponding to each energy consumption factor to the parameter included in the first parameter. Estimation method. A characteristic evaluation method for evaluating a driving characteristic related to energy consumption of a mobile body or a characteristic related to energy consumption of the mobile body based on the second parameter estimated by the parameter estimation method according to claim 2,
The characteristic evaluation section
Obtaining a second parameter estimated by the parameter estimation method;
Based on the relative size of the parameter included in the second parameter, the influence of the energy consumption factor that gives the weighting of the energy consumption is determined by the parameter, so that the driving characteristic related to the energy consumption of the moving object or the movement A characteristic evaluation method characterized by evaluating characteristics related to energy consumption of a body.   The characteristic evaluation unit is a parameter that gives a weighting of energy consumption corresponding to a parameter that defines an energy consumption factor depending on acceleration / deceleration of the moving body, included in the first parameter, of the second parameters. The characteristic evaluation method according to claim 3, wherein when the relative magnitude is larger than the other parameters in the second parameter, it is evaluated that the energy consumption is high.   The characteristic evaluation unit includes a parameter for defining an energy consumption factor depending on a moving time of a moving body in each section on the route, included in the first parameter among the second parameters, and each parameter on the route Parameters that specify energy consumption factors that depend on the distance traveled by the moving body in the section, parameters that define energy consumption factors that depend on the altitude difference in each section on the route, and that the moving body receives in each section on the route The relative size of the parameter that gives the weight of the energy consumption corresponding to at least one of the parameters defining the energy consumption factor depending on the air resistance is larger than the other parameters in the second parameter The characteristic evaluation method according to claim 3, wherein the characteristic relating to the energy consumption of the mobile body is evaluated according to whether or not the mobile object is used. A history information acquisition unit that acquires movement history information including energy consumption of a moving body consumed by moving a route, route information of the route, and a moving state of the moving body in the route;
A parameter estimation unit that estimates a second parameter by the parameter estimation method according to claim 1 or 2 using the movement history information acquired by the history information acquisition unit;
A navigation apparatus comprising: a route search processing unit that performs a route search in consideration of energy consumption based on the second parameter estimated by the parameter estimation unit.

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