JP5314617B2 - Fuel efficiency improvement index calculation device and navigation system - Google Patents

Description

  The present invention relates to a fuel efficiency improvement index calculation device and a navigation system that generate an index used for driving determination of a driving method with good fuel efficiency.

  Petroleum fuels such as gasoline and light oil are used to drive the engine that powers the vehicle, but in order to improve the economy when the vehicle is running, the fuel consumption is improved, that is, the fuel consumption (for example, There is a demand for a good driving distance (mileage per liter of gasoline).

  By the way, the fuel consumption is influenced by the road conditions during driving and the driving method of the driver, and it is possible to improve the fuel consumption by economical route selection to the destination and driving. Therefore, conventionally, in order to make the driver perform economical driving, a technique for accurately calculating the fuel consumption in an arbitrary measurement target traveling section has been proposed.

  For example, in Patent Document 1, the travel distance signal calculated from the speed signal and the fuel signal of the liquid level sensor that senses the current remaining fuel level are taken out at the start and end of measurement, The fuel consumption is calculated by using the distance data and the fuel data.

Japanese Patent Laid-Open No. 10-90037 (see FIG. 1, paragraphs 0014 to 0017)

  However, in the technique described in Patent Document 1, the travel distance between two points is merely divided by the amount of consumed fuel, and the speed change based on the travel pattern in the travel section is not sufficiently considered. However, it was not enough as an indicator of good driving.

  The present invention solves the above-described conventional problems, and quantifies the continuity of a running pattern based on a change in speed of a running section, and generates an index used for driving judgment of a driving method with good fuel efficiency. It is to provide a degree index calculation device and a navigation system.

  In order to solve the above-described problem, the present invention provides a fuel efficiency improvement index calculating device that calculates an index of a driving method with good fuel efficiency of a traveling vehicle, the vehicle speed calculating unit for calculating the vehicle speed of the vehicle, and the vehicle speed The first time series in which the time series are arranged and the second time series in which the time series of the first time series are shifted are formed, and the time series correlation difference between the vehicle speeds in the first time series and the second time series And a display processing unit that visualizes the time-series correlation difference of the vehicle speed with a recurrence plot and displays it as an index.

  According to the present invention, it is possible to use as an index of driving with good fuel consumption by visualizing a running pattern with a vehicle speed analysis unit and a recurrence plot.

  Further, according to the present invention, when there is a large difference in the count value of the frequency at which the time-series correlation difference between the vehicle speeds before and after the vehicle speed pattern suddenly changes is less than a predetermined value, there is a high possibility that congestion will occur in the future. It is characterized by estimating.

  According to the present invention, it is possible to predict a traffic jam from a running pattern visualized by a vehicle speed analysis unit and a recurrence plot.

  Further, the present invention is a navigation system, wherein a vehicle speed acquisition unit that acquires a vehicle speed of a vehicle, a first time series in which a time series of the vehicle speed is arranged, and a second time series in which the time series of the first time series are shifted. A route selection information generating unit that forms a time series, calculates a time-series correlation between vehicle speeds in the first time series and the second time series, and generates route selection information by visualization using a recurrence plot; And a route selection information providing unit that provides route selection information to the vehicle.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to provide a driving | running | working area with good fuel consumption as a navigation system by visualizing a driving | running pattern with a vehicle speed analysis part and a recurrence plot.

  Further, the present invention is characterized in that the route selection information generating unit and the route selection information providing unit are provided at least in a server in a navigation system.

  According to the present invention, since the server can receive the vehicle speed data from the vehicle and visualize it by the vehicle speed analysis unit and the recurrence plot, it is optimal for improving the fuel consumption up to the destination with respect to other vehicles. A travel route can be provided.

  The present invention also includes a vehicle speed calculation unit that calculates a vehicle speed of the vehicle, the vehicle speed is formed in a first time series and a second time series that is shifted from the first time series, and the first time series A vehicle speed analysis unit that calculates a time series correlation difference of the vehicle speed with the second time series, a processing unit that visualizes the time series correlation difference of the vehicle speed by a recurrence plot, and a time series correlation difference of the visualized vehicle speed. A transmission unit that transmits data as data, and a navigation system that collects and uses the data transmitted from a vehicle, and collects and collects the data from a plurality of vehicles, and routes using the aggregated data A route selection information generating unit that generates selection information, and a route selection information providing unit that provides the route selection information to a vehicle.

  According to the present invention, the server can collect the data visualized by the recurrence plot from each vehicle and provide an optimal travel route for improving the fuel efficiency to the destination for other vehicles. .

  According to the present invention, there is provided a fuel efficiency improvement index calculation device and a navigation system that quantify the continuity of a driving pattern based on a change in speed of a driving section and generate an index used for driving determination of a driving method with good fuel efficiency. It becomes possible.

It is a figure which shows the fuel consumption improvement index calculation apparatus which concerns on 1st Embodiment. It is a figure which shows the relationship between the vehicle speed V and time T, (a) is a driving | running pattern showing steady driving | running | working, (b) is a driving | running pattern showing unsteady driving | running | working. It is a flowchart which shows the creation procedure of a recurrence plot, (a) shows the storage process of vehicle speed data, (b) shows the drawing process of recurrence plot. It is the figure which quantified FIG. 2 by the recurrence plot. It is the figure which quantified the continuity / unsteadiness of the running pattern of each running section. It is a figure which shows the navigation system which concerns on 2nd Embodiment. It is a figure which shows the example of a display of the driving | running route in which regular driving | running | working is possible.

  Hereinafter, a fuel efficiency improvement index calculation device and a navigation system according to an embodiment of the present invention will be described in detail with reference to the drawings.

(First embodiment)
FIG. 1 is a diagram showing a fuel efficiency improvement index calculating apparatus according to the first embodiment.
The fuel efficiency improvement index calculation device 10 according to the present embodiment quantifies the driving pattern of one vehicle from the autocorrelation function of the vehicle speed, calculates the index and provides it to the driver, and determines the driving method of driving with good fuel efficiency. It is used for.

  For example, the fuel efficiency improvement index calculation device 10 may be used by being incorporated in a navigation device such as a car navigation device. By incorporating the fuel efficiency improvement index calculation device 10, the navigation device has the function of displaying a map including the current location on the display unit based on the map data, and the optimum route from the viewpoint of improving fuel efficiency from the departure point to the destination. It is possible to provide a function of providing an index so that the driver can proceed. Here, the map data for road display on the map used in the navigation device includes node data and link data. Here, the node is a point where a link such as an intersection intersects, and the link is a road connecting these nodes. The link and the node are examples, and there is no particular limitation on where the road starts and ends to calculate the fuel consumption.

  The fuel efficiency improvement calculation device 10 includes a vehicle speed calculation unit 11, a vehicle speed analysis unit 12, and a display processing unit 13 in order to quantify the fuel efficiency improvement level.

  The vehicle speed calculation unit 11 calculates the vehicle speed V every moment and outputs it to the vehicle speed analysis unit 12. The vehicle speed V is, for example, stored in a plurality of storage areas (not shown) sequentially with periodic data of vehicle speed pulses from a vehicle speed pulse sensor at an arbitrary timing, and the vehicle speed V is calculated from each periodic data stored in each storage area. Calculate. The calculated vehicle speed V is stored in a storage unit such as a RAM (Random Access Memory).

The vehicle speed analysis unit 12 uses the above-described vehicle speed V to change the vehicle speed difference between the first time series and the second time series into a two-dimensional array variable D (i, j) as shown in Expression 1. The result of calculating is stored. Here, i and j are 0 or a positive integer. In Equation 1, i represents the first time series, and j represents the second time series.

D (i, j) = | V (i) −V (j) |

In Formula 1, for example, i is first fixed to 0, j is set to 0, 1, 2, 3,..., N (n is 0 or a positive integer), and the first time series and the first time series (N + 1) vehicle speed differences | V (0) −V (n) | Next, i is fixed to 1, j is set to 0, 1, 2, 3,..., N (n is 0 or a positive integer), and | V (1) −V (n) | (N + 1) pieces are calculated. This is repeated until i becomes n.

  Next, similarly, j is fixed to 0. First, i is set to 0, 1, 2, 3,..., N (n is 0 or a positive integer). (N + 1) vehicle speed differences | V (n) −V (0) | Next, j is fixed to 1, i is set to 0, 1, 2, 3,..., N (n is 0 or a positive integer), and | V (n) −V (0) | (N + 1) pieces are calculated. This is repeated until j becomes n.

  FIG. 2 illustrates the relationship between the vehicle speed V and the time T. A change in the vehicle speed V over time T is shown. FIG. 2A shows a steady traveling pattern, and FIG. 2B shows an unsteady traveling pattern. The traveling pattern shown in FIG. 2 (a) is stable for a longer time than the traveling pattern shown in FIG. 2 (b) at the time of high speed and low speed (steady), and the traveling pattern of FIG. 2 (b). It can be seen that the pattern is unstable (unsteady) with many transitions from low speed to high speed and from high speed to low speed.

  The display processing unit 13 uses the D (i, j) calculated by Expression 1 to quantify and visualize the recurrence plot. Recurrence plot is a proposed method for visually analyzing complex time series data. Using this technique, D (i, j) is plotted in black or white according to the value. For example, black is plotted when D (i, j) <ε, and white is plotted when D (i, j) ≧ ε, with a threshold ε indicating a predetermined vehicle speed difference. The value of ε can be appropriately set as a value that improves fuel consumption by experiments and simulations.

The above processing will be supplementarily described with reference to a flowchart showing a procedure for creating a recurrence plot in FIG.
First, the data (vehicle speed data) shown in FIG. 2 is stored in the storage unit by the process of FIG. The process of FIG. 3A will be described. First, 0 is set as an initial value of h, which is a loop counter (S1). Note that h is a loop counter in the flowchart and an index of V (h) that is a one-dimensional array variable.

  Subsequently, the vehicle speed V, that is, the current vehicle speed Vnow is calculated from the vehicle speed pulse obtained during traveling. The calculated vehicle speed Vnow is stored in V (h) (S3) and stored in the storage unit (S4). Then, h is incremented by one (S5). If the process is not completed in step S6, the process returns to step S2 (S6 → No), and steps S3 to S5 are repeated to sequentially store V (h). On the other hand, if the process is finished in step S6 (S6 → Yes), the vehicle speed data storage process is finished. Incidentally, the processing in FIG. 3A is performed by the vehicle speed calculation unit 11.

  The termination condition in step S6 is when the value of h reaches a predetermined value or when the travel time or travel distance reaches a certain value. However, when the recurrence plot of FIG. 4 is created, The value (predetermined value) of h is 600, that is, it is sufficient if there is 600 V (h). Here, for example, if sampling is performed point by point at intervals of 10 seconds, V (h) for 600 points, that is, V (0) to V (600) is obtained by the vehicle traveling for 6000 seconds (100 minutes). can get.

Next, the recurrence plot shown in FIG. 4 is created by the processing of FIG.
In this process, first, 0 is set as an initial value of the loop counters i and j (S11). Subsequently, the vehicle speed data V (i) and V (j) stored by the processing of FIG. 3A is read from the storage unit (S12). Incidentally, since the vehicle speed data to be read first is i = j = 0, both V (i) and V (j), which are one-dimensional array variables, are V (0) and naturally have the same value. Become.

After step S12, the operation result of | V (i) −V (j) | is stored in D (i, j) which is a two-dimensional array variable (S13), and the calculated D (i, j) is obtained. It is determined whether it is smaller than the threshold value ε (S14). If D (i, j) is smaller than the threshold ε (S14 → Yes), a flag of black is set in D (i, j) (S15). On the other hand, if D (i, j) is equal to or greater than the threshold ε (S14 → No), a flag of white is set in D (i, j) (S16). Incidentally, when i = j = 0, both V (i) and V (j) are V (0), that is, V (i) and V (j) have the same value, so D (0 , 0) becomes 0 (S14 → No), and a white flag is set in D (i, j) (S15).
Supplementally, when i and j are the same value, V (i) and V (j) are always the same value, and as a result, D (i, j) is always 0.

  In the next step S17, D (i, j) for which black or white is set (after black and white is set) is stored in the storage unit. The stored D (i, j) is sequentially read out in step S22 to be described later and drawn as a recurrence plot.

  After storing D (i, j) in step S17, the value of i is incremented by one (S18). Then, it is determined whether or not i after the increment is larger than n. If it is larger, the process proceeds to step S20 (S19 → Yes). On the other hand, if i is n or less, the process proceeds to step S12, and the process is repeated with the incremented value of i (S19 → No).

If i> n (S19 → Yes), the value of j is incremented by one, i is set to 0 (zero) (S20), and the process is repeated until j> n. That is, if j is n or less (S21 → No), the process proceeds to step S12 and the process is repeated with the incremented value of j. On the other hand, if j is larger than n (S21 → Yes), the process proceeds to step S22.
Incidentally, if the recurrence plot of FIG. 4 is a 550 × 550 dot matrix, both the value of n in step S19 and the value of n in step S21 may be 549.

In step S22, a recurrence plot is drawn according to the value of D (i, j) for which black or white is set (S22). That is, i, j is sequentially changed from 0 to n, D (i, j) corresponding to the changed i, j is read from the storage unit, and black or white is set to the coordinates i, j of the recurrence plot. Strike and draw. For example, i is the coordinate on the horizontal axis of the recurrence plot, and j is the coordinate on the vertical axis of the recurrence plot.
3B is performed by the vehicle speed analysis unit 12, and the process of S22 is performed by the display processing unit 13.

  Incidentally, when step S14 is Yes, black dots are plotted at the positions of the coordinates i and j of the recurrence plot. Steps S15 and S16 are not particularly necessary. When Step S14 is Yes, if black is immediately plotted at the position of the coordinates i and j of the recurrence plot, Steps S16 and S17 (and further S22). ) Can be omitted. In other words, when step S14 is Yes, it may be plotted immediately.

FIG. 4 is a diagram visualizing FIG. 2 by a recurrence plot. In FIG. 4, the horizontal axis is represented by i, the vertical axis is represented by j, the plotting position is defined, D (i, j) <ε is plotted in black, and D (i, j) ≧ ε is white. Plotting.
A region surrounded by a circle in FIG. 2A represents steady running while moving at a high speed with little speed change. 4 (a) corresponding to this, since the speed change is small, D (i, j) = | V (i) −V (j) | becomes smaller, so D (i, j ) <Ε increases, and the area plotted in black increases.

In FIG. 4 (b), as shown in FIG. 2 (b), D (i, j) = | V (i) −V (j) | ) ≧ ε in many cases, and there are fewer places to plot in black than in FIG.
Thus, by calculating the time-series correlation difference between the first time series and the second time series and visualizing the running pattern with the recurrence plot, it can be used as an index of driving with good fuel consumption. .

  Next, traffic jam prediction will be described. In the process of forming a traffic jam, there is an unsteady traffic flow called mixed flow in the process from a free flow in which the vehicle is flowing smoothly to a traffic flow that is the flow of the vehicle at the time of traffic jam. . Therefore, it is possible to predict traffic congestion by capturing the mixed flow. In the mixed flow, movement of the vehicle called a Stop-Go (SG) wave has been confirmed. The SG wave creates a backward propagation that prevents the vehicle from moving in the traveling direction, and increases the deceleration trend of the vehicle. The traveling pattern having an unsteady state that creates this deceleration trend is the source of the traffic jam.

  FIG. 5 is a diagram quantifying the continuity / non-stationarity of the travel pattern of each travel section. In the graph obtained from the relationship between the vehicle speed and time shown in FIG. 2A, the frequency at which D (i, j) <ε is counted for each travel section (1-5) index. That is, the points plotted in black in the recurrence plot shown in FIG. 4 are counted.

In the travel section indexes 2 and 5, the count number is as high as 70 to 80, indicating that the travel is steady travel (free flow) with little speed change. Index 3 shows a low value of 10 to 20 counts, and there is an unsteady flow with many speed changes. In the transition process from index 2 to 3, the movement of the vehicle called a Stop-Go (SG) wave is confirmed, and the presence of the mixed flow is confirmed.
Thus, when there is a large difference in the number of counts with a frequency such that D (i, j) <ε before and after the vehicle speed pattern suddenly changes, there is a high possibility that a traffic jam will occur within a few minutes in the future.

  According to the first embodiment, the travel pattern can be visualized by the recurrence plot on the basis of the speed change in the travel section, and an index used for driving determination of the driving method with good fuel efficiency can be provided. In addition, it is possible to predict a traffic jam from the quantified travel pattern.

(Second Embodiment)
FIG. 6 is a diagram showing a navigation system according to the second embodiment. In addition, about the structure or function similar to 1st Embodiment, the duplication of the description may be abbreviate | omitted.

  The navigation system 20 includes a vehicle 30 that generates vehicle speed data among data for calculating a fuel efficiency improvement index, and a server 40 that receives the data from the vehicle 30 and calculates a fuel efficiency improvement index. The difference from the first embodiment is that the server 40 receives the vehicle speed data calculated by the vehicle speed calculation unit 32 from the vehicle 30, calculates the value of D (i, j) by the autocorrelation function, and D (i , J) <ε is counted and quantified by the recurrence plot.

  The vehicle 30 includes a vehicle speed calculation unit 32 and a vehicle communication unit 31. Here, the vehicle speed calculation unit 32 is the same as the vehicle speed calculation unit 11 described in the first embodiment, and a description thereof will be omitted. The server 40 includes a route selection information providing unit 41, a route selection information generating unit 42, and a server communication unit 43.

The vehicle speed data of the vehicle 30 is transmitted to the server 40 via the vehicle communication unit 31.
When the server communication unit 43 receives vehicle speed data from the vehicle 30, the server 40 calculates D (i, j) <ε based on Equation 1 in the route selection information generation unit 42 and quantifies it by the recurrence plot. To do.
The route selection information providing unit 41 determines whether the traveling pattern of the vehicle is a steady traveling or an unsteady traveling based on D (i, j) in a plurality of vehicles quantified by the route selecting information generating unit 42. A travel route capable of steady travel is provided for the vehicle.

  FIG. 7 is a diagram illustrating a display example of a travel route in which steady travel is possible. The server 40 transmits to the host vehicle traveling on the link B the fuel efficiency improvement index for the vehicle traveling on the link C and the vehicle traveling on the link D. As shown in FIG. 7, the driver can recognize that the traveling pattern of the link C is capable of steady traveling with less speed change than the traveling pattern of the link D, and the driver can determine to travel on the link C. .

  In the present embodiment, the vehicle speed data is calculated by the vehicle speed calculation unit 32 in the vehicle. However, even if the server 40 includes the vehicle speed calculation unit 32 and calculates the vehicle speed using the vehicle speed pulse received from the vehicle. Good.

  According to the present embodiment, the server 40 receives vehicle speed data from the vehicle 30, calculates D (i, j) <ε, and based on this, can be visualized by a recurrence plot. On the other hand, it is possible to provide an optimal travel route for improving the fuel efficiency to the destination.

(Other embodiments)
In the second embodiment, the vehicle speed data is received from the vehicle. For example, a plurality of data visualized by the recurrence plot from the vehicle of the first embodiment are collected and totaled, and the totalized quantification is performed. Needless to say, the navigation system may include a route selection information generation unit that generates route selection information using data and a route selection information provision unit that provides route selection information to the vehicle.

DESCRIPTION OF SYMBOLS 10 Fuel consumption improvement index calculation apparatus 11 Vehicle speed calculating part 12 Vehicle speed analyzing part 13 Display processing part 20 Navigation system 30 Vehicle 31 Vehicle communication part 32 Vehicle speed calculating part 40 Server 41 Route selection information providing part 42 Route selection information generating part 43 Server communication part (Vehicle speed acquisition part)

Claims (5)

A fuel efficiency improvement index calculating device for calculating an index of a driving method with good fuel efficiency of a traveling vehicle,
A vehicle speed calculation unit for calculating the vehicle speed of the vehicle;
Forming a first time series in which the vehicle speed time series is arranged and a second time series in which the time series of the first time series are shifted;
A vehicle speed analyzer that calculates a time-series correlation between vehicle speeds in the first time series and the second time series;
A fuel efficiency improvement index calculation apparatus comprising: a display processing unit that visualizes the time-series correlation difference of the vehicle speed by a recurrence plot and displays the index as an index. It is estimated that there is a high possibility of traffic jams in the future when there is a large difference in the count value of the frequency at which the time-series correlation difference between the vehicle speeds before and after the vehicle speed pattern suddenly changes is less than a predetermined value. The fuel consumption improvement index calculation device according to claim 1. A navigation system,
A vehicle speed acquisition unit for acquiring the vehicle speed;
Forming a first time series in which the vehicle speed time series is arranged and a second time series in which the time series of the first time series are shifted;
A route selection information generating unit that calculates a time-series correlation between vehicle speeds in the first time series and the second time series, and generates route selection information by visualization using a recurrence plot;
A navigation system comprising: a route selection information providing unit that provides the vehicle with the route selection information. The navigation system according to claim 3 , wherein the route selection information generating unit and the route selection information providing unit are provided at least in a server in the navigation system. A vehicle speed calculator for calculating the vehicle speed,
The vehicle speed is formed in a first time series and a second time series obtained by shifting the first time series,
A vehicle speed analysis unit that calculates a time-series correlation of vehicle speeds in the first time series and the second time series;
A processing unit for visualizing the time-series correlation difference of the vehicle speed by a recurrence plot;
A transmission unit that transmits the time-series correlation of the visualized vehicle speed as data, and a navigation system that collects and utilizes the data transmitted from the vehicle,
A route selection information generating unit that collects and aggregates the data from a plurality of vehicles, and generates route selection information using the aggregated data;
A navigation system comprising: a route selection information providing unit that provides the vehicle with the route selection information.

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