JP2010044755A - Support system, method and program for assessing environmental load - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method and a program for assessing an environmental load and also a system for assessing the environmental load to support the assessment of reduction and current state of carbon dioxide being emitted from a running automobile. <P>SOLUTION: A server control unit 21 for an environmental load assessment supporting server 20 divides collected sample data into a short trip, evaluates a speed pattern, and also analyzes the short trip, wherein a typical speed pattern typically representing an equal occurrence frequency for each automobile running state group is predetermined to generate a representative speed pattern. Next, a client terminal 10 specifies a corresponding representative speed pattern based on an input automobile running information, estimates a time-series change of running speed and torque, and also estimates an amount of carbon dioxide. In addition, the client terminal 10 obtains digital tachograph data, specifies a sudden start or a wave like running of the automobile, replaces the specified one with a representative speed pattern having a reduced environmental load, and compares the reduced environmental load with an environmental load without any reduction. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an environmental load evaluation support system, an environmental load evaluation support method, and an environmental load evaluation support program for supporting an assessment of the current state of carbon dioxide emissions during driving of an automobile and an evaluation for reduction.

  Today, the impact of carbon dioxide emissions on the environment is drawing attention. For example, an environmental impact simulation apparatus for supporting the construction of an environment-coexisting region by simulating the effects of facilities and equipment on the environment has been studied (for example, see Patent Document 1). In the environmental impact simulation apparatus described in this document, a plurality of parameter values related to a system including facilities and equipment are input. Based on the input parameter value, the cost related to the system is calculated. Furthermore, based on the input parameter value, the amount of carbon dioxide released from the system to the environment in a predetermined period is calculated, and the calculated cost and amount are stored.

  In the field of automobiles, attempts have been made to evaluate carbon dioxide emissions. For example, the Ministry of the Environment has published a gasoline and diesel heavy vehicle speed conversion program for measures against automobiles in the atmospheric environment (see, for example, Non-Patent Document 1). By using this program, torque and rotation speed are calculated by taking into account air resistance, acceleration resistance, rolling resistance, and gradient resistance from driving characteristics consisting of speed and acceleration, operating characteristics consisting of loaded weight, and vehicle characteristics. can do.

  Further, a technique for calculating the carbon dioxide emission amount by a known engine map analysis using the torque and the rotational speed calculated using the vehicle speed conversion program is being studied (for example, see Non-Patent Document 2).

JP 2000-556 A (first page)

Ministry of the Environment, "Vehicle speed conversion program for gasoline and diesel heavy vehicles", [online], [Search June 20, 2008], Internet, <URL: http://www.env.go.jp/air/car /program/index.html> Independent Administrative Institution, Traffic Safety and Environment Research Institute, “Development of CO2 Emissions Evaluation Program for Automotive Field”, [online], [Search June 20, 2008], Internet, <URL: http: //www.ntsel. go.jp/ronbun/happyoukai/forum2007files/3_forum2007_.pdf>

  By the way, when evaluating the influence of carbon dioxide emitted from automobiles, it is necessary to consider an automobile transportation company having many commercial automobiles. However, automobile carriers have various business scales, business forms, and management forms. For this reason, in the transportation business of each company, it was difficult to accurately grasp the amount of carbon dioxide emitted from transportation vehicles.

  In addition, in order to calculate the carbon dioxide emission accurately, detailed information on the vehicle and the operation state is necessary. However, if the detailed information is input manually, the workload increases. For this reason, it is desirable that the carbon dioxide emission can be calculated with as simple an input as possible.

  Furthermore, it is also possible to propose a driving method for reducing the load on the environment by providing the driver or business operator with information about the environmental impact of the driving by his / her driving.

  The present invention has been made to solve the above-mentioned problems, and its purpose is to provide an environmental load evaluation support system, an environmental load for supporting the current grasp of carbon dioxide emissions during driving of a vehicle and an evaluation for reduction. To provide an evaluation support method and an environmental load evaluation support program.

  In order to solve the above-mentioned problems, the invention according to claim 1 is characterized in that the operation record data storage means for recording the travel history about the travel speed during operation and the representative analysis pattern variable value corresponding to the travel state group. An environmental load evaluation support system comprising speed pattern data storage means for recording a representative speed pattern every time and control means for calculating the amount of carbon dioxide discharged based on the running speed, wherein the control means Trips constituting the travel history recorded in the operation record data storage means are developed into short trips separated by a temporary stop state where the travel speed becomes “0”, and the size of each short trip for each short trip. For the travel history recorded in the operation record data storage means, and the accumulated frequency of the analysis pattern variable values The cloth is calculated, the axis representing the cumulative frequency in the cumulative frequency distribution is divided into equal intervals with a constant width, and each short trip corresponding to the representative analysis pattern variable value consisting of the statistical value of each interval has the same appearance frequency. The gist is to identify the speed pattern, record it in the speed pattern data storage means in association with the traveling state group of each short trip, and calculate the carbon dioxide emission using this representative speed pattern.

  According to a second aspect of the present invention, in the environmental load evaluation support system according to the first aspect of the present invention, when the control means acquires an evaluation target in which the magnitude of the trip is specified, the control means is made to correspond to the traveling state group. The representative analysis pattern variable values of the representative speed pattern are sequentially combined until the evaluation target trip size is reached, and the evaluation is performed using the carbon dioxide emission corresponding to the representative speed pattern. To do.

  According to a third aspect of the present invention, in the environmental load evaluation support system according to the first or second aspect, the control means performs a frequency analysis in each short trip, calculates a frequency distribution of amplitudes, and sets the traveling state group. Correspondingly, a statistical value of the frequency distribution of the amplitude is calculated, a short trip is reconstructed using the statistical value of the frequency distribution of the amplitude, and a representative speed pattern is generated using the reconstructed short trip. This is the gist.

  According to a fourth aspect of the present invention, in the environmental load evaluation support system according to any one of the first to third aspects, the control means obtains an evaluation object in which a travel history about a traveling speed during operation is recorded. In this case, the amount of carbon dioxide emitted is calculated based on the traveling speed, and the trips that constitute the traveling history are developed into short trips that are separated by a pause state where the traveling speed becomes “0”. For each short trip, in the speed pattern data storage means, a representative speed pattern with a small amount of carbon dioxide emissions is identified in correspondence with the running state group, and the carbon dioxide emissions when this representative speed pattern is replaced are compared with each other. As a summary.

  The invention according to claim 5 is the environmental load evaluation support system according to claim 4, wherein the control means calculates an acceleration at the start of each short trip, and the acceleration is a short trip with a reference value or more. The gist is to execute replacement with a representative speed pattern with a low carbon dioxide emission.

  The invention according to claim 6 is the environmental load evaluation support system according to claim 4 or 5, wherein the control means calculates an acceleration energy equivalent per unit distance in each short trip, and the acceleration energy equivalent is a reference. The gist is to replace the short trip above the value with a representative speed pattern with a low carbon dioxide emission.

  The invention according to claim 7 is the environmental load evaluation support system according to any one of claims 4 to 6, wherein the control means calculates a time interval between short trips, and the time interval is a reference time. The gist is to replace the above short trips with a speed pattern when idling is stopped.

  The gist of the invention described in claim 8 is that the time required for a short trip is used as the analysis pattern variable value in the environmental load evaluation support system according to any one of claims 1 to 7.

  The gist of the ninth aspect of the invention is that the environmental load evaluation support system according to any one of the first to seventh aspects uses a travel distance in a short trip as the analysis pattern variable value.

  The invention according to claim 10 is the operation record data storage means for recording a travel history about the travel speed during operation, and the speed at which the representative speed pattern is recorded for each representative analysis pattern variable value corresponding to the travel state group. A method for supporting environmental load evaluation using an environmental load evaluation support system comprising pattern data storage means and control means for calculating the amount of carbon dioxide emitted based on travel speed, wherein the control means Expands the trips constituting the travel history recorded in the operation record data storage means into short trips separated by a pause state where the travel speed is “0”, and for each short trip, An analysis pattern variable value representing the magnitude of the travel pattern recorded on the travel record data storage means is calculated for the analysis pattern variable The cumulative frequency distribution is calculated, the axis representing the cumulative frequency in the cumulative frequency distribution is divided into equal intervals with a constant width, and each short trip corresponding to the representative analysis pattern variable value consisting of the statistical value of each interval appears Are identified as the same representative speed pattern, recorded in the speed pattern data storage means corresponding to each short trip traveling state group, and the carbon dioxide emission is calculated using this representative speed pattern.

According to the eleventh aspect of the present invention, an operation record data storage means for recording a travel history about a travel speed during operation, and a speed at which a representative speed pattern is recorded for each representative analysis pattern variable value corresponding to a travel state group. A program for supporting evaluation of environmental load using an environmental load evaluation support system comprising pattern data storage means and control means for calculating the amount of carbon dioxide emitted based on the running speed, the control means Are expanded into short trips that are separated by a temporary stop state where the running speed is “0”, and each short trip is tripped for each short trip. An analysis pattern variable value representing the size of the travel pattern is calculated and the analysis pattern is recorded on the travel history recorded in the travel record data storage means. The cumulative frequency distribution of the variable values is calculated, the axis representing the cumulative frequency in the cumulative frequency distribution is divided into equal intervals with a constant width, and each short trip corresponding to the representative analysis pattern variable value consisting of the statistical value of each interval is calculated. It is specified as a representative speed pattern having the same appearance frequency, is recorded in the speed pattern data storage means in correspondence with the traveling state group of each short trip, and functions as a means for calculating the carbon dioxide emission amount using this representative speed pattern. This is the gist.

(Function)
According to the invention described in claim 1, 10 or 11, the control means delimits trips constituting the travel history recorded in the operation record data storage means in a pause state where the travel speed is “0”. To develop a short trip. Next, for each short trip, an analysis pattern variable value representing the magnitude of each short trip is calculated, and a cumulative frequency distribution of the analysis pattern variable value is calculated for the travel history recorded in the operation record data storage means. Next, the axis representing the cumulative frequency in the cumulative frequency distribution is divided into equal intervals with a constant width, and each short trip corresponding to the representative analysis pattern variable value consisting of the statistical value of each interval is set as a representative speed pattern having the same appearance frequency. It is specified and recorded in the speed pattern data storage means in correspondence with the traveling state group of each short trip. Then, the carbon dioxide emission is calculated using this representative speed pattern. Here, the magnitude of the short trip can be represented by the travel distance and travel time in the short trip. A variety of driving histories are recorded in the operation record data storage means depending on the operation, but it is subdivided by short trips, and by using short trips with the same appearance frequency, representative driving patterns are generated. can do.

  According to the second aspect of the present invention, when the control means obtains the evaluation target in which the magnitude of the trip is specified, the control means corresponds to the traveling state group until the trip size of the evaluation target is reached. The representative analysis pattern variable values of the representative speed pattern are sequentially combined. Then, the evaluation is performed using the carbon dioxide emission corresponding to the representative travel pattern. Thereby, even when there is no detailed information about the operation, it is possible to estimate the traveling state to be evaluated using the representative speed pattern and evaluate the load on the environment.

  According to the invention described in claim 3, the control means performs frequency analysis in each short trip, calculates the frequency distribution of the amplitude, and calculates the statistical value of the frequency distribution of the amplitude corresponding to the traveling state group. . Then, the short trip is reconstructed using the statistical value of the frequency distribution of the amplitude, and the representative speed pattern is generated using the reconstructed short trip. In wavy running that frequently accelerates and decelerates, a large amplitude occurs at a high frequency. Therefore, the running pattern corresponding to the running state group can be expressed using the analysis result of the frequency analysis.

  According to the invention described in claim 4, when the control means obtains the evaluation object in which the traveling history of the traveling speed during operation is recorded, the amount of carbon dioxide discharged based on the traveling speed is calculated. To do. Then, the trips constituting the travel history are developed into short trips separated by a pause state in which the travel speed is “0”. Next, for each short trip, in the speed pattern data storage means, a representative speed pattern with a small amount of carbon dioxide emission is identified in correspondence with the running state group, and the carbon dioxide emission amount when replaced with this representative speed pattern Is output as a comparison result. Thereby, the traveling method with a smaller environmental load can be proposed.

  According to the invention described in claim 5, the control means calculates the acceleration at the start of each short trip, and replaces the short trip whose acceleration is equal to or higher than the reference value with a representative speed pattern with a small amount of carbon dioxide emission. Execute. As a result, it is possible to compare and output the evaluation results of the actual driving and the driving with suppressed sudden start, and to propose a traveling method with a smaller environmental load.

According to the sixth aspect of the present invention, the control means calculates the acceleration energy equivalent per unit distance in each short trip, and the short speed when the acceleration energy equivalent is a reference value or more is represented by a representative speed with a small amount of carbon dioxide emission. Perform replacement with pattern. As a result, it is possible to propose a traveling method with a smaller environmental load by comparing and outputting the evaluation results of the actual driving and the driving in which the wavy running is suppressed.

  According to the seventh aspect of the present invention, the control means calculates the time interval between short trips, and executes the replacement with the speed pattern when idling is stopped between the short trips whose time interval is equal to or greater than the reference time. To do. As a result, it is possible to propose a traveling method with a smaller environmental load by comparing and outputting the evaluation results for the actual driving and the driving with the idle stop suppressed.

  According to the eighth aspect of the invention, the time required for the short trip is used as the analysis pattern variable value. Thereby, the running state of the evaluation target can be estimated using the short trip time.

  According to the invention described in claim 9, the travel distance in the short trip is used as the analysis pattern variable value. Thereby, the running state of the evaluation target can be estimated using the short trip distance.

  ADVANTAGE OF THE INVENTION According to this invention, the present condition grasp | ascertainment of the carbon dioxide emission amount in driving | running | working of a motor vehicle and the evaluation with respect to reduction can be supported.

The system schematic of embodiment of this invention. Explanatory drawing of the functional block of an environmental load evaluation support server. Explanatory drawing of the functional block of a client control part. Illustration of the relationship between trip chain, trip, and short trip. Explanatory drawing of the collection sample data recorded on the sample database. Explanatory drawing of the vehicle record contained in collection sample data. Explanatory drawing of the operation record contained in collection sample data. Explanatory drawing of the driving record contained in collection sample data. Explanatory drawing of the data recorded on the speed pattern database. Explanatory drawing of a typical driving | running | working pattern. Explanatory drawing of the process sequence of this embodiment. Explanatory drawing of the process sequence of this embodiment. Explanatory drawing of the process sequence of this embodiment. Explanatory drawing of the process sequence of this embodiment. Explanatory drawing of the process sequence of this embodiment. Explanatory drawing of required input items and optional input items. Explanatory drawing of the functional block of a reduction assistance means. Explanatory drawing of the process sequence of this embodiment. Explanatory drawing of the process sequence of this embodiment. It is explanatory drawing of the production | generation of the representative driving | running pattern in other embodiment, Comprising: (a) is division | segmentation of a short trip, (b) is the frequency analysis result of a cruise part, (c) is explanatory drawing of reconstruction of a representative driving pattern. . Explanatory drawing of the process sequence of other embodiment. Explanatory drawing of the process sequence of other embodiment. Explanatory drawing of the block used for the classification of trip.

(First embodiment)
Hereinafter, an embodiment embodying the present invention will be described with reference to FIGS. In the present embodiment, it is assumed that the evaluation for the reduction of the emission amount of carbon dioxide (CO2) in the traveling of the automobile is supported. In the present embodiment, as shown in FIG. 4, various events such as loading and unloading are performed during the period from leaving (first event) to entering (last event). And the driving | running | working between each event is called a "trip", and a series of trips included in this driving | operation is called a trip chain. In addition, each trip is composed of a short period of travel separated by a temporary stop of travel (for example, stop by a red light). In the present embodiment, the short-term traveling that constitutes each trip is called a short trip. And this short trip is used to evaluate the impact on the environmental impact of driving the car.

  For this evaluation, as shown in FIG. 1, an environmental load evaluation support server 20 and a client terminal 10 connected to each other via a network (Internet) are used. The environmental load evaluation support server 20 and the client terminal 10 function as an environmental load evaluation support system and execute an environmental load evaluation support simulation.

  The server control unit 21 of the environmental load evaluation support server 20 includes control means such as a CPU (not shown) and memories such as RAM and ROM. Specifically, the following processing (short trip development stage, short trip analysis stage, representative travel pattern calculation stage, CO2 emission calculation stage, program distribution stage, etc.) is performed. By executing the environmental load evaluation support program for this purpose, as shown in FIG. 2, the server control unit 21 of the environmental load evaluation support server 20 performs a short trip developing unit 211, a short trip analyzing unit 212, and a representative travel pattern calculation. Functions as a means 213, a CO2 emission amount calculation means 214, and a program distribution means 215.

The short trip developing means 211 executes a process of developing the travel history of the automobile into a short trip.
The short trip analysis means 212 executes processing for analyzing the travel of the developed short trip.

The representative travel pattern calculation means 213 executes processing for generating a representative travel pattern using the analyzed statistical value of the short trip.
The CO2 emission amount calculation means 214 executes a process for calculating the carbon dioxide emission amount using the calculated representative travel pattern.
The program distribution unit 215 executes processing for distributing a program and data for evaluating the environmental load to the client terminal 10.

  Further, as shown in FIG. 1, the environmental load evaluation support server 20 includes a sample database 22, a speed pattern database 23, a representative travel pattern database 24, an input support database 25, a conversion coefficient database 26, an emission basic unit database 27, an evaluation, and the like. A program data storage unit 28 is provided.

The sample database 22 functions as operation record data storage means, and records a travel history (collected sample data) collected from various automobile carriers. As shown in FIG. 5, in the collected sample data, an operation record 222 and a travel record 223 are recorded for the vehicle record 221. Here, in the vehicle record 221, data relating to the characteristics of the automobile used in the transportation business is recorded, and specifically, registered based on matters described in the vehicle verification. The operation record 222 records data related to the contents of transportation requested by the customer. Specifically, the operation record 222 is registered based on items described in a daily driving report, a dispatch card, and the like. The travel record 223 records data related to travel in each service, and specifically, is registered based on the data recorded in the travel digital tachograph collected from each car carrier. The

As shown in FIG. 6, the vehicle record 221 includes data on a vehicle number, a vehicle type, a maximum load capacity, a total vehicle weight, and a fuel type.
In the vehicle number data area, data relating to an identifier for identifying a car used by a car carrier is recorded.

  In the vehicle type data area, data relating to an identifier for specifying the vehicle type of the automobile is recorded. By using this vehicle type information, vehicle characteristics can be acquired from a vehicle type database (not shown) in which specification data is recorded for each type of vehicle.

In the maximum load amount data area, data relating to the maximum amount that can be loaded in the automobile is recorded.
In the total vehicle weight data area, data relating to the total weight including the loads and passengers of the automobile is recorded.

  In the fuel type data area, data relating to an identifier for specifying the fuel of the automobile is recorded. In this embodiment, data relating to an identifier for specifying gasoline or diesel is recorded. In addition, the kind of fuel of a motor vehicle is not limited to these.

  On the other hand, as shown in FIG. 7, the operation record 222 includes data (operation content record) for specifying the operation content using each vehicle and data (event record) for specifying an event included in each operation. ) Is recorded. The operation content record includes data relating to a vehicle number, an operation number, an operation date, a start distance, and an end distance. Further, the event record is recorded for each event included in the operation. This event record includes data related to event occurrence time, event content, event required time, departure time, travel time, travel distance, cargo load weight, filling rate, empty vehicle / actual vehicle identification flag, and transport item.

In the vehicle number data area, data relating to an identifier for specifying the automobile that has acquired the travel history during transportation is recorded.
In the operation number data area, data relating to an identifier for specifying each operation for transportation using the automobile is recorded.

In the operation date data area, data relating to the date for specifying the date of each operation is recorded.
In the start distance and end distance data areas, data relating to the travel distance (for example, odometer) at the end of the operation is recorded. From the difference between the end distance and the start distance, the travel distance of the day can be calculated.

In the event occurrence time data area, data related to the time when the event occurred is recorded.
In the event content data area, data for specifying the content of the event is recorded. In the present embodiment, event contents include “shipping”, “warehousing”, “loading”, “unloading”, “inspection”, “break”, “fueling”, and the like.

Data relating to the time required for this event is recorded in the event required time data area.
In the departure time data area, data relating to the time at which the event ends and the vehicle starts to travel is recorded.

In the travel time and travel distance data areas, data related to the time and distance traveled from the end of this event to the next event occurrence are recorded.
In the cargo loading weight data area, data relating to the cargo loading / unloading weight at the time of the event occurrence is recorded.

In the filling rate data area, data relating to the filling rate (volume ratio) of the loaded cargo in the loading platform of the automobile is recorded.
In the empty vehicle / actual vehicle identification flag data area, a flag (empty vehicle flag or actual vehicle flag) for identifying the load state of the package from the end of the event to the next event occurrence is recorded.
In the transport item data area, when this event is loading or unloading, data relating to an item for specifying the type of the loaded package is recorded.

  Further, as shown in FIG. 8, the travel record 223 includes data (operation content record) for specifying the operation content using each vehicle, and data (travel record record) that records the driving situation included in each operation. ) Is recorded. Similar to the operation record 222, the operation content record includes data relating to the vehicle number, operation number, operation date, start distance, and end distance. Furthermore, the traveling record record is recorded every time the traveling state is sampled. This traveling record record includes data related to sampling time, speed, engine speed, traveling distance, position information, acceleration, acceleration time, and idling time.

In the sampling time data area, data relating to the sampling time is recorded.
In the speed, engine speed, and travel distance data areas, data relating to the speed, engine speed, and travel distance at the sampling time are recorded, respectively.

  In the position information data area, data relating to the location of the vehicle at the sampling time is recorded. In the present embodiment, as position information, data relating to latitude and longitude acquired using, for example, GPS (Global Positioning System) is recorded.

In the acceleration data area, data relating to the acceleration of the vehicle at the sampling time is recorded.
In the acceleration time data area, data relating to the time during which the acceleration is continued is recorded. This acceleration time is recorded when the measurement of elapsed time from the start of acceleration is started and the end of acceleration is detected.

  In the idling time data area, data relating to the duration of idling is recorded. This idling time is recorded when the measurement of elapsed time from the start of idling is started and idling stop is detected.

  The speed pattern database 23 functions as a speed pattern data storage means, and records speed pattern records 230 in various running state groups in a short trip extracted from the collected sample data, as shown in FIG. This speed pattern record 230 is recorded when the representative speed pattern of each traveling state group is specified. The speed pattern record 230 includes data related to the representative speed pattern for each short trip time in association with the empty / actual vehicle identification flag, the sudden start identification flag, and the wavy travel identification flag.

In the empty vehicle / actual vehicle identification flag area, data relating to an identifier for identifying an empty vehicle or an actual vehicle is recorded.
In the sudden start identification flag area, data relating to an identifier for identifying the presence or absence of a sudden start is recorded.

In the wavy running identification flag area, data relating to an identifier for identifying the presence or absence of wavy running is recorded.
In the representative speed pattern area, data on a speed pattern in each short trip is recorded for each short trip time as a representative analysis pattern variable value. The speed pattern is composed of data indicating a change in speed with respect to the time axis.

  In the representative travel pattern database 24, a representative travel pattern record representing the representative travel pattern in each travel state is recorded. As will be described later, this representative travel pattern record is recorded when a typical travel pattern is generated using typical short trips in various travel states. As shown in FIG. 10, this representative traveling pattern is configured by combining typical short trips (speed patterns). Then, by using this representative travel pattern, it is possible to calculate the engine speed, the torque, and finally the carbon dioxide emission.

  In the input support database 25, input support data for supplementing information necessary for speed conversion is recorded with respect to information on the essential input items input through the simple input screen. In the input support database 25, data regarding default values is recorded for each option input item included in the option input screen. In the input support database 25, for example, an average loading rate statistically calculated from the collected sample data is recorded for the transport item. By using this average loading rate, the loading weight can be calculated from the maximum loading weight.

  In this embodiment, vehicle characteristics and operation characteristics are input on a simple input screen or option input screen. Required input items for the vehicle characteristics of this simple input include “vehicle number”, “model number”, “type of fuel”, “model of motor”, “vehicle size (vehicle length, vehicle width, vehicle height) ”,“ Weight (maximum loading capacity, vehicle weight, total vehicle weight) ”and the like. Required input items for operation characteristics include “vehicle number”, “loading information (number of loading / unloading, transport item, loading status at the time of loading, loading status at the time of loading)”, “travel information (travel distance, operating time, Use a break).

  As optional input items of the vehicle characteristics of the optional input, “transmission ratio (gear ratio)”, “engine characteristics (maximum torque rotation speed, full load characteristics, no load characteristics)” and the like are used. Optional input items for travel characteristics include "trip required time", "loading weight", "number of passengers", "travel time", "travel distance", "travel time zone", "travel area", "working time, etc." (Loading / unloading time, waiting time, break time) "," idle time (loading / unloading time, waiting time, break time, signal / congestion stop time) "and the like are used.

  In the input support database 25, the default value (statistical value of the collected sample data) when the optional input item is not set for the essential input item and the data related to the conversion formula for performing the vehicle speed conversion are recorded. Has been. In this embodiment, statistical values (average loading rate, average work time, average idle time) calculated corresponding to the transport item are recorded.

  In the conversion coefficient database 26, conversion coefficients for calculating torque and engine speed from the running characteristics, operation characteristics, and vehicle characteristics in the known vehicle speed conversion program described in Non-Patent Document 1 are recorded.

In the emission basic unit database 27, data relating to an engine map for calculating the amount of carbon dioxide emitted at the input torque and engine speed is recorded. In this engine map, data relating to the basic unit of carbon dioxide discharged per unit time is recorded corresponding to the torque and the engine speed.

  The evaluation program data storage unit 28 stores an environmental load evaluation support program for evaluating carbon dioxide emissions at each client terminal 10. This environmental load evaluation support program is distributed to the client terminal 10 of each automobile carrier via the Internet.

  On the other hand, the client terminal 10 is a user's computer terminal that uses the environmental load evaluation support server 20 to evaluate its own environmental load. In the present embodiment, an automobile transportation company is assumed as a user. The client terminal 10 has a function of transmitting data via the Internet, a function of displaying received data, and the like. For this reason, the client terminal 10 includes an input unit such as a keyboard and a mouse, an output unit such as a display, a communication unit, and the like in addition to a CPU, RAM, and ROM (not shown).

  The client control unit 11 of the client terminal 10 includes control means such as a CPU (not shown) and memories such as RAM and ROM. Specifically, the processes described later (input control stage, calculation control stage, output control stage, reduction support stage processes, etc.) are performed. By executing the environmental load evaluation support program for this purpose, as shown in FIG. 3, the client control unit 11 of the client terminal 10 has an input control unit 11a, a calculation control unit 11b, an output control unit 117, and a reduction support unit 119. Function as.

The input control unit 11a includes a simple input unit 111, an option input unit 112, and a digital data input unit 118.
The calculation control means 11b includes a default value setting means 113, a speed pattern estimation means 114, a vehicle speed conversion means 115, and a CO2 calculation means 116.

The simple input means 111 executes a screen output process for supporting input of essential input items for calculating carbon dioxide emission.
The option input means 112 executes a screen output process for supporting input of optional input items that are insufficient for speed conversion with respect to essential input items for simple input.

The default value setting means 113 executes a support process that supplements the contents of items not set in the option input items.
The speed pattern estimation unit 114 executes a speed pattern estimation process in this operation based on the input information.

The vehicle speed conversion means 115 is realized by a vehicle speed conversion program, and executes a calculation process of torque and engine speed using the travel characteristics, operation characteristics, and vehicle characteristics.
The CO2 calculation means 116 executes a calculation process of carbon dioxide emission using the torque and engine speed calculated by the vehicle speed conversion means 115.

The output control unit 117 executes control processing for outputting the calculated evaluation result.
The digital data input means 118 executes the digital tachograph data receiving process when the automobile carrier records the digital tachograph data.

The reduction support means 119 executes an evaluation process for traveling for reducing the amount of carbon dioxide emission. As shown in FIG. 17, the reduction support means 119 includes a short trip development means 119a, a sudden start detection means 119b, a wavy running detection means 119c, an idle stop detection means 119d, a speed pattern replacement means 119e, and an evaluation output means 119f. Is done.

  The short trip developing unit 119a executes a process of developing the travel data included in the digital tachograph data acquired by the digital data input unit 118 into a short trip, like the short trip developing unit 211.

The sudden start detection means 119b executes processing for determining whether or not there is a sudden start based on the acquired digital tachograph data.
The wavy running detection means 119c executes processing for determining the presence or absence of wavy running based on the digital tachograph data.

  The idle stop detection means 119d executes processing for determining whether or not an idle stop is necessary based on the digital tachograph data. For this reason, the idle stop detection means 119d holds a reference time for determining necessity.

When the speed pattern replacement unit 119e determines that an operation with a large environmental load is being performed, the speed pattern replacement unit 119e executes a process of replacing the speed pattern with a speed pattern that reduces the environmental load with respect to such an operation.
The evaluation output unit 119f executes a process of outputting an evaluation result for traveling in this operation including a speed pattern with a reduced environmental load.

  Further, as shown in FIG. 3, the client terminal 10 includes an input support database 12, a speed pattern database 13, a conversion coefficient database 14, and an emission basic unit database 15. Each database is recorded when each data is acquired from the environmental load evaluation support server 20.

  Similar to the input support database 25, the input support database 12 records input support data for supplementing information necessary for speed conversion with respect to information on the essential input items input through the simple input screen.

  Similar to the speed pattern database 23, the speed pattern database 13 records speed pattern records in various running states in order to calculate the carbon dioxide emission amount.

  Similar to the conversion coefficient database 26, the conversion coefficient database 14 stores conversion coefficients for calculating torque and engine speed from the running characteristics, operation characteristics, and vehicle characteristics in a known vehicle speed conversion program.

  Similarly to the emission basic unit database 27, the emission basic unit database 15 records data relating to an engine map for calculating the amount of carbon dioxide emitted at the input torque and engine speed.

  The processing procedure for supporting the evaluation of environmental load using the system configured as described above will be described with reference to FIGS. Here, first, an outline (FIG. 11) will be described, and processing (FIGS. 12 to 14) executed in the environmental load evaluation support server 20 and processing (FIGS. 15, 18, and 19) executed in the client terminal 10 will be described. Detailed description.

(Overview)
First, an outline of environmental load evaluation support will be described with reference to FIG.
Here, the server control unit 21 of the environmental load evaluation support server 20 executes representative travel pattern generation processing (step S1-1). Specifically, the short trip development means 211, the short trip analysis means 212, and the representative travel pattern calculation means 213 of the server control unit 21 use the collected sample data to determine whether the vehicle is in an empty / actual vehicle state, whether there is a sudden start or wave-like travel. A representative speed pattern is calculated for each divided traveling state group. Then, the server control unit 21 combines the representative speed patterns to generate a representative travel pattern.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes a representative travel pattern evaluation process (step S1-2). Specifically, the CO2 emission calculation means 214 of the server control unit 21 calculates the load (carbon dioxide emission) on the environment in the generated representative travel pattern.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes distribution processing of the environmental load evaluation support program (step S1-3). Specifically, the program distribution means 215 of the server control unit 21 distributes an environmental load evaluation support program and various databases to each client terminal 10 of the car carrier. Each client terminal 10 stores the received environmental load evaluation program and various databases in a data storage unit in the client terminal 10.

  Next, the client control unit 11 of the client terminal 10 executes an evaluation process by simple input by starting an environmental load evaluation program (step S1-4). Specifically, the client control unit 11 calculates a carbon dioxide emission amount based on various information input by the car carrier.

  Next, the client control unit 11 of the client terminal 10 executes an evaluation process using digital tachograph data (step S1-5). Specifically, the client control unit 11 calculates the carbon dioxide emission amount based on the digital tachograph data input by the automobile carrier.

(Representative driving pattern evaluation process)
Next, a representative travel pattern evaluation process in the environmental load evaluation support server 20 will be described with reference to FIG.

  Here, the server control part 21 of the environmental load evaluation support server 20 performs the extraction process of the operation data of evaluation object (step S2-1). Specifically, the short trip developing means 211 of the server control unit 21 extracts the operation record 222 to be evaluated from the sample database 22 and records the vehicle number, operation number, departure time, event recorded in the operation record 222. The required time and the actual / empty vehicle identification flag are specified.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes a process of extracting evaluation target travel data (step S2-2). Specifically, the short trip developing unit 211 of the server control unit 21 specifies the travel record 223 in which the specified vehicle number and operation number are recorded, and extracts the sampling data of the travel record record for the required time from the departure time. To do. In this case, the short trip developing means 211 performs grouping based on the actual vehicle / empty vehicle identification flag recorded in the operation record 222 and temporarily stores the travel record 223 in the memory. In the present embodiment, this loaded state (classification of actual vehicle / empty vehicle) is one of the elements that determine the traveling state group.

Next, the server control unit 21 of the environmental load evaluation support server 20 executes a disassembly process into short trips in the travel data (step S2-3). Specifically, the short trip analysis unit 212 of the server control unit 21 specifies a suspension time zone in which the speed is “0” in the extracted travel record 223. And the short trip analysis means 212 identifies each short trip by dividing | segmenting the trip recorded on the driving record 223 by the area pinched | interposed by this temporary stop time slot | zone.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes a signal waiting time calculation process in the travel data (step S2-4). Specifically, the short trip analysis means 212 of the server control unit 21 specifies the temporary stop time zone as the signal waiting time. Then, the short trip analysis means 212 calculates a statistical value (here, an average value) of the signal waiting time and temporarily stores it in the memory.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes a speed pattern evaluation process (step S2-5). In this embodiment, as will be described later, it is determined by this speed pattern evaluation process whether there is suppression of sudden start or suppression of wave running. In the present embodiment, whether or not the sudden start is suppressed or whether or not the wave-like traveling is suppressed is one of the factors that determine the traveling state group.

  Further, the server control unit 21 of the environmental load evaluation support server 20 executes a short trip analysis process (step S2-6). In this embodiment, as will be described later, the cumulative frequency of the short trip time (the magnitude of the short trip) is calculated for each traveling state group, and a typical short trip (representative speed pattern) in which the appearance frequency of each short trip is equal. Is identified.

  And the server control part 21 of the environmental load evaluation assistance server 20 performs the calculation process of a short trip distance for every short trip (step S2-7). Specifically, the short trip analysis unit 212 of the server control unit 21 calculates the travel distance in each short trip by time-integrating the speeds constituting the specified short trip.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes representative travel pattern generation processing (step S2-8). Specifically, the representative travel pattern calculation unit 213 of the server control unit 21 typically has the same appearance frequency for each traveling state group identified by the presence or absence of suppression of sudden start, the presence or absence of suppression of wavelike traveling, and the loading state. A representative traveling pattern is generated by combining typical short trips (representative speed patterns). Then, the representative traveling pattern calculation unit 213 records each generated representative traveling pattern record in the representative traveling pattern database 24 for each traveling state group.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes a carbon dioxide emission calculation process for the representative travel pattern (step S2-9). Specifically, the CO2 emission calculation means 214 of the server control unit 21 introduces the travel characteristics, operation characteristics, and vehicle characteristics of each representative travel pattern for each travel state group into a known vehicle speed conversion program. Here, speed and acceleration specified by the representative travel pattern are used as the travel characteristics. Further, as the operation characteristic, an average load weight calculated according to the empty vehicle / actual vehicle identification flag is used. Further, as the vehicle characteristics, the specified front projection area, transmission gear ratio, tire diameter, and engine characteristics corresponding to the vehicle type specified by the vehicle record 221 are used. Then, the carbon dioxide emission amount is calculated by performing a known engine map analysis using the torque and the engine speed calculated by the vehicle speed conversion program.

Then, the CO2 emission calculating means 214 calculates the carbon dioxide emission per unit distance by dividing the carbon dioxide emission calculated for each representative travel pattern by the total travel distance in each representative travel pattern. Then, the CO2 emission amount calculation means 214 records the carbon dioxide emission amount calculated for each traveling state group in the representative traveling pattern database 24.

(Speed pattern evaluation process)
Next, the speed pattern evaluation process will be described with reference to FIG.
Here, the short trips to be evaluated are sequentially identified, and the following processing is repeated for each short trip.

  First, the server control unit 21 of the environmental load evaluation support server 20 executes acceleration calculation processing at the time of starting (step S3-1). Specifically, the short trip analysis means 212 of the server control unit 21 specifies sampling data of the travel record record included in the short trip to be evaluated, and acquires the acceleration at the start in the sampling data. This acceleration can also be calculated by differentiating the speed at the start acceleration included in the sampling data.

Next, the server control unit 21 of the environmental load evaluation support server 20 executes an acceleration energy equivalent calculation process per unit distance (step S3-2). Specifically, the short trip analysis means 212 of the server control unit 21 is the time of the next sample in the continuous sampling data in the travel record included in the short trip to be evaluated at the next sampling speed (Vi). The data interval (data interval: Δt) in which the speed (Vi + 1) of the current is increasing is specified. Then, the acceleration energy equivalent is calculated by the following equation.
[Acceleration energy equivalent] = Σ (([Vi + 1] ^ 2- [Vi] ^ 2) / Δt)

  Then, the short trip analysis unit 212 calculates an acceleration energy equivalent per unit distance by dividing the total value by the travel distance of the short trip. The above processing is repeated for each short trip to be evaluated.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes a sort process based on acceleration at the time of start (step S3-3). Specifically, the short trip analysis means 212 of the server control unit 21 performs the short trips temporarily stored in the memory for each group classified based on the actual vehicle / empty vehicle identification flag in order of increasing acceleration at the time of starting. Line up.

  Then, the server control unit 21 of the environmental load evaluation support server 20 executes a pattern extraction process of “the sudden start is suppressed” (step S3-4). Specifically, the short trip analysis unit 212 of the server control unit 21 suppresses a sudden start in each group temporarily stored in the memory by a short trip in which the order of acceleration at the start is less than 25% from the lowest. The group is subdivided by specifying as the pattern.

  In addition, the server control unit 21 of the environmental load evaluation support server 20 executes a pattern extraction process of “no sudden start suppression” (step S3-5). Specifically, the short trip analysis unit 212 of the server control unit 21 suppresses a sudden start in each group temporarily stored in the memory by a short trip in which the order of acceleration at the start is 75% or more from the smallest one. The group is subdivided by specifying as a pattern not to be performed.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes a sort process based on an acceleration energy equivalent per unit distance (step S3-6). Specifically, the short trip analysis means 212 of the server control unit 21 arranges the short trips in the order of decreasing acceleration energy equivalent per unit distance in each subdivided group.

Then, the server control unit 21 of the environmental load evaluation support server 20 “suppresses the wavy running”
The pattern extraction process is executed (step S3-7). Specifically, the short trip analysis means 212 of the server control unit 21 performs the wave trip on the short trip in which the order of the acceleration energy equivalent per unit distance is 25% or less in each subdivided group. Identify and extract as a suppressed pattern.

In addition, the server control unit 21 of the environmental load evaluation support server 20 executes a pattern extraction process of “no wave-like travel suppression” (step S3-8). Specifically, the short trip analysis means 212 of the server control unit 21 performs the wave trip on the short trip in which the order of the acceleration energy equivalent per unit distance is 75% or more in each subdivided group. It identifies and extracts as a pattern which is not suppressed.
As described above, from each group classified based on the presence / absence of the actual vehicle / empty vehicle identification flag, a traveling state group subdivided according to the presence / absence of suppression of sudden start and the presence / absence of suppression of wavelike traveling is generated.

(Short trip analysis process)
Next, the short trip analysis process will be described with reference to FIG. This process is executed for each group divided into running state groups.

  First, the server control unit 21 of the environmental load evaluation support server 20 executes processing for calculating the cumulative frequency of short trip times (step S4-1). Specifically, the short trip analysis unit 212 of the server control unit 21 calculates a relative cumulative frequency distribution with the horizontal axis representing the short trip time and the vertical axis representing the cumulative frequency. In this case, in the relative cumulative frequency distribution, the cumulative frequency corresponding to the short trip with the longest short trip time is 100%.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes a short trip time section division process so that the relative cumulative frequency is constant (step S4-2). Specifically, the short trip analysis unit 212 of the server control unit 21 divides the cumulative frequency axis of the relative cumulative frequency distribution into sections at regular intervals. In the present embodiment, it is assumed that the cumulative frequency axis is divided into 10 sections by dividing the maximum value (100%) of the cumulative frequency axis at regular intervals (in this case, 10% each).

  Then, the server control unit 21 of the environmental load evaluation support server 20 executes typical short trip specifying processing for each section of the short trip time (step S4-3). Specifically, the short trip analysis means 212 of the server control unit 21 calculates a statistical value for a section divided at regular intervals. In the present embodiment, the median value of the divided sections is used as the statistical value. Thereby, it is possible to specify the short trip time (representative analysis pattern variable value) having the same appearance frequency in each traveling state group. Then, as described above, the representative traveling pattern is calculated for each traveling state group by combining the speed patterns of the short trip time having the same appearance frequency. Carbon dioxide emissions are calculated using this representative travel pattern.

(Simple evaluation process)
Next, the simple evaluation process will be described with reference to FIG. This process is executed in the client terminal 10 of the car carrier. For this reason, the client terminal 10 downloads data and programs used for environmental load evaluation from the environmental load evaluation support server 20. Then, the downloaded environmental load evaluation support program is executed in the client terminal 10.

In this case, the client control unit 11 of the client terminal 10 executes various information specifying processing (step S5-1). Specifically, the simple input unit 111 of the client control unit 11 outputs a simple input screen for setting essential input items on the display of the client terminal 10. The essential input items include various items of vehicle characteristics and travel characteristics as shown in FIG. The simple input screen is provided with a setting field for inputting these items.

  When the simple input unit 111 detects the completion of input to each setting field, the process is transferred to the option input unit 112. In this case, the option input means 112 outputs an option input screen for setting option input items on the display.

  Setting of this optional input item is arbitrary. Therefore, the user can make various inputs by himself / herself, but the input can be omitted. And the option input means 112 acquires the various information input in the option input screen. Here, for the setting field that is left blank on the option input screen, the default value setting means 113 obtains information about items that are not set (items that are missing) from the input support database 12 and supplements them.

  Specifically, the average loading rate is specified from the simple input transport items, and the maximum loading weight by simple input is multiplied to calculate the loading weight. Further, the travel distance, trip required time, and idle time of each trip are estimated using the statistical values recorded in the input support database 12 from the simple input travel distance, operation time, loading / unloading count, and loading state.

  Next, the client control unit 11 of the client terminal 10 executes a representative speed pattern specifying process (step S5-2). Specifically, the speed pattern estimation means 114 of the client control unit 11 is based on the information set by the simple input means 111, the option input means 112, and the default value setting means 113 for trips included in the operation to be evaluated. Identify mileage and loading status for each trip. Then, the speed pattern estimation unit 114 specifies a representative speed pattern corresponding to the loading state of each trip in the speed pattern database 13.

  Next, the client control unit 11 of the client terminal 10 executes time-series change estimation processing for the traveling speed (step S5-3). Specifically, the speed pattern estimation unit 114 of the client control unit 11 uses the representative speed pattern recorded in the speed pattern database 13 until the actual travel time (trip size) of this operation is reached. The representative speed patterns are combined in order from the shortest time. When the sum of the short trip times exceeds the actual travel time, the speed pattern estimation means 114 returns the result before combining the last representative speed patterns, and identifies the representative speed pattern whose sum is closest to the actual travel time. Join again. Thereby, the speed pattern estimation means 114 estimates a time-series change in the traveling speed based on the combined representative speed pattern.

  Next, the client control unit 11 of the client terminal 10 executes a torque time series change estimation process (step S5-4). Specifically, the speed pattern estimation unit 114 of the client control unit 11 calculates acceleration from the time-series change of the estimated traveling speed, and supplies information on the speed and acceleration to the vehicle speed conversion unit 115. In this case, the vehicle speed conversion means 115 uses the conversion coefficient database 14 to calculate time-series changes in torque and engine speed from the speed and acceleration.

And the client control part 11 of the client terminal 10 performs the estimation process of a carbon dioxide emission amount (step S5-5). Specifically, the CO2 calculating means 116 of the client control unit 11 calculates the carbon dioxide emission amount from the time series change of the torque and the engine speed using the engine map recorded in the emission amount basic unit database 15. Then, the output control means 117 of the client control unit 11 outputs the calculated carbon dioxide emission amount as an evaluation result.

(Digital tachograph evaluation process)
Next, the evaluation process using digital tachograph data will be described with reference to FIGS.

  Here, as shown in FIG. 18, the client control unit 11 of the client terminal 10 executes an actual travel data acquisition process (step S6-1). Specifically, the digital data input unit 118 of the client control unit 11 acquires digital tachograph data for the operation to be evaluated.

  Next, the client control unit 11 of the client terminal 10 executes a disassembly process into short trips (step S6-2). Specifically, the short trip developing means 119a of the client control unit 11 specifies the section delimited by the pauses in the travel data recorded in the digital tachograph, as with the short trip developing means 211, and performs a short trip. Disassembled into

  Next, the client control unit 11 of the client terminal 10 executes a torque time-series change estimation process (step S6-3). Specifically, the vehicle speed conversion means 115 of the client control unit 11 calculates time series changes in torque and engine speed from the speed and acceleration included in each short trip using the conversion coefficient database 14.

  Next, the client control unit 11 of the client terminal 10 executes a carbon dioxide emission estimation process (step S6-4). Specifically, the CO2 calculating means 116 of the client control unit 11 calculates the carbon dioxide emission amount from the time series change of the torque and the engine speed using the engine map recorded in the emission amount basic unit database 15.

  Next, the client control unit 11 of the client terminal 10 executes an environmental load reduction simulation (step S6-5). Specifically, the reduction support means 119 of the client control unit 11 executes processing described later.

(Environmental impact reduction simulation)
Here, the environmental load reduction simulation will be described with reference to FIG. In this process, first, the following process is repeated for each short trip.

  The client control unit 11 of the client terminal 10 executes acceleration calculation processing at the time of starting (step S7-1). Specifically, the sudden start detection means 119b of the client control unit 11 calculates the acceleration at the start of the short trip recorded in the digital tachograph data.

  Further, the client control unit 11 of the client terminal 10 executes an acceleration energy equivalent calculation process per unit distance (step S7-2). Specifically, the wavy running detection means 119c of the client control unit 11 calculates the acceleration energy equivalent per unit distance in the short trip recorded in the digital tachograph data, as in step S3-2.

Next, the client control unit 11 of the client terminal 10 executes a determination process as to whether or not the vehicle is suddenly started (step S7-3). Specifically, the sudden start detection unit 119b of the client control unit 11 determines that the sudden start is suppressed when the acceleration at the start is equal to or less than a reference value. In the present embodiment, the maximum value of the acceleration of the “pattern in which sudden start is suppressed” recorded in the speed pattern database 13 is used as the reference value.

  Here, when it is determined that the sudden start is suppressed (in the case of “YES” in Step S7-3), the client control unit 11 of the client terminal 10 performs a determination process as to whether or not the vehicle is traveling in a wavy manner (Step S7-3). S7-4). Specifically, the wavy running detection unit 119c of the client control unit 11 determines that the wavy running is suppressed when the acceleration energy equivalent per unit distance is equal to or less than the reference value. In the present embodiment, the maximum value of the acceleration energy equivalent per unit distance of the “pattern in which the wavy running is suppressed” recorded in the speed pattern database 13 is used as the reference value.

  Here, when it is determined that the wave traveling is suppressed (in the case of “YES” in Step S7-4), the client control unit 11 of the client terminal 10 ends the process for this short trip.

  On the other hand, when it is determined that the sudden start is not suppressed (in the case of “NO” in Step S7-3), or when it is determined that the wave running is not suppressed (in the case of “NO” in Step S7-4). The client control unit 11 of the client terminal 10 executes a speed pattern replacement process (step S7-5). Specifically, the speed pattern replacement means 119e of the client control unit 11 uses the “speed pattern that suppresses sudden start” and the “speed pattern that suppresses wave running” from the speed pattern database 13 for this short trip. The representative speed pattern with the shortest short trip distance is extracted. The speed pattern in which the sudden start and the wave-like traveling are suppressed corresponds to a representative speed pattern with a small amount of carbon dioxide emission.

The process so far is repeated for all short trips included in the operation recorded in the digital tachograph data.
Next, the following processing is repeated for each temporary stop for the short trip.

  Here, the client control unit 11 of the client terminal 10 executes a determination process as to whether or not the suspension time is equal to or longer than the reference time (step S7-6). Specifically, the idle stop detection means 119d of the client control unit 11 calculates the length of the pause time between short trips. Then, the idle stop detection means 119d compares with the held reference time.

  Here, when the pause time is equal to or longer than the reference time (in the case of “YES” in step S7-6), the idle stop detection means 119d of the client control unit 11 executes the idle stop replacement process (step S7-7). ). Specifically, the speed pattern replacement unit 119e of the client control unit 11 replaces the speed pattern with idling stopped during this temporary stop period.

On the other hand, if the temporary stop time has not reached the reference time (in the case of “NO” in step S7-6), the idle stop detection means 119d maintains the original pattern.
The process so far is repeated for every short trip interval recorded in the digital tachograph data. As described above, speed pattern data (simulation pattern) is simulated which simulates a sudden start, a wavy running, and an idling stop.

And the client control part 11 of the client terminal 10 performs a result output process (step S7-8). Specifically, the evaluation output unit 119f of the client control unit 11 supplies the simulation pattern to the vehicle speed conversion unit 115 to calculate the torque and the engine speed. Further, the torque and engine speed are supplied to the CO2 calculating means 116 to calculate the carbon dioxide emission amount.

  Then, the evaluation output unit 119f acquires the carbon dioxide emission calculated using the digital tachograph data and the carbon dioxide emission of the simulation pattern. Furthermore, the evaluation output unit 119f generates screen data that compares the carbon dioxide emission amount due to actual traveling with the carbon dioxide emission amount due to traveling of the simulation pattern, and outputs the screen data to the display of the client terminal 10.

According to this embodiment, the following effects can be obtained.
-In this embodiment, the server control part 21 of the environmental load evaluation assistance server 20 performs the production | generation process of a representative driving | running | working pattern using the sample data collected from the motor vehicle carrier (step S1-1). Then, the server control unit 21 of the environmental load evaluation support server 20 executes a representative travel pattern evaluation process (step S1-2). Thereby, the general tendency of the amount of carbon dioxide emitted by the operation of the automobile in the automobile transportation company can be grasped. In particular, it is possible to calculate the increase / decrease in carbon dioxide emission due to the presence or absence of suppression of sudden start or wave running, and evaluate the influence on the environment.

  -In this embodiment, the server control part 21 of the environmental load evaluation assistance server 20 performs the decomposition | disassembly process to a short trip (step S2-3), and a short trip analysis process (step S2-6). Here, the short trip time is analyzed for each traveling state group, and a typical short trip having the same appearance frequency of each short trip is specified. Then, the server control unit 21 of the environmental load evaluation support server 20 executes a representative travel pattern generation process (step S2-8) and a carbon dioxide emission calculation process (step S2-9) of the representative travel pattern. Thus, it is possible to identify typical short trips from collected sample data composed of various short trips, generate a representative traveling pattern considering the appearance frequency, and calculate the carbon dioxide emissions of this pattern. it can.

  -In this embodiment, the server control part 21 of the environmental load evaluation assistance server 20 performs a speed pattern evaluation process (step S2-5). Here, the server control unit 21 of the environmental load evaluation support server 20 executes acceleration calculation processing at the time of start (step S3-1) and acceleration energy equivalent calculation processing per unit distance (step S3-2). And the server control part 21 of the environmental load evaluation support server 20 performs the sort process by the acceleration at the time of start (step S3-3) and the sort process by the acceleration energy equivalent per unit distance (step S3-6). Thereby, based on the collected sample data, it is possible to statistically grasp the driving situation such as sudden start and wave running.

  -In this embodiment, the client control part 11 of the client terminal 10 performs the evaluation process by simple input by starting an environmental load evaluation program (step S1-4). In this case, the client control unit 11 of the client terminal 10 executes various information specifying processing (step S5-1). Here, for the setting fields that are left blank on the option input screen, the default value setting means 113 obtains information about items that are not set from the input support database 12 and supplements them. Thereby, the automobile carrier can efficiently evaluate the environmental load by setting only information on the essential input items. In addition, an automobile carrier that knows the detailed information can perform more accurate evaluation by setting option input items.

-In this embodiment, the client control part 11 of the client terminal 10 performs the actual driving | running | working data acquisition process (step S6-1), the decomposition | disassembly process to a short trip (step S6-2). Then, the client control unit 11 of the client terminal 10 executes torque time-series change estimation processing (step S6-3) and carbon dioxide emission estimation processing (step S6-4). Thereby, it is possible to calculate the carbon dioxide emission amount based on the actual operation and evaluate the environmental load.

  -In this embodiment, the client control part 11 of the client terminal 10 performs a reduction simulation process (step S6-5). Here, the client control unit 11 of the client terminal 10 executes acceleration calculation processing at the time of start (step S7-1) and acceleration energy equivalent calculation processing per unit distance (step S7-2). When it is determined that the sudden start is not suppressed (in the case of “NO” in step S7-3), or when it is determined that the undulating travel is not suppressed (in the case of “NO” in step S7-4), the client The client control unit 11 of the terminal 10 executes a speed pattern replacement process (step S7-5). Therefore, by acquiring digital tachograph data, it is possible to specify whether or not sudden start or wave-like traveling is suppressed for traveling on each short trip, and to calculate the carbon dioxide emissions when driving with a small environmental load is performed. .

  Moreover, the client control part 11 of the client terminal 10 performs the determination process about whether it is more than reference time about the temporary stop which exists between short trips (step S7-6). If the pause time is equal to or longer than the reference time (in the case of “YES” in step S7-6), the idle stop detection means 119d of the client control unit 11 executes idle stop replacement processing (step S7-7). . Therefore, by acquiring digital tachograph data, it is possible to determine whether or not there is an idle stop, and to calculate the carbon dioxide emissions when an operation with a small environmental load is performed.

In addition, you may change each said embodiment as follows.
○ In the above embodiment, the travel time was used to evaluate the magnitude of trips and short trips. However, the index indicating the “size” is not limited to this. It is also possible to use travel distance.

  In the above embodiment, the presence / absence of the wavy running is determined based on the acceleration energy equivalent per unit distance, but the method for determining the presence / absence of the wavy running is not limited to this. For example, it is possible to make a determination using an integral value of acceleration during acceleration in a short trip. Furthermore, it is also possible to determine by the acceleration energy equivalent per unit time.

  In the above embodiment, the running state group is classified by the empty vehicle / actual vehicle identification flag, the sudden start identification flag, and the wavy running identification flag. The classification of the driving state group is not limited to these, and can be classified according to the presence / absence of “highway use”, “traveling area”, and “time zone”.

  ○ In the above embodiment, a short trip that is 25% or less from the lowest acceleration order at the time of start is specified as a “pattern that suppresses sudden start”, and a short trip that is 75% or more is “not suppressed sudden start” Specified as "pattern". In addition, a short trip that is 25% or less from the smallest acceleration energy equivalent order per unit distance is specified as a “pattern that suppresses wavy travel”, and a short trip that is 75% or more is “a pattern that does not suppress wavy travel” ". Here, the reference value for generating the running state group is not limited to “25%” or “75%”. By keeping the reference value determined for classification in the short trip analysis means 212, each short trip can be classified by using this reference value depending on whether or not sudden start or wave-like traveling is suppressed.

  In the above embodiment, the load weight is calculated by specifying the average load ratio from the simple input transport items and multiplying the maximum load weight. The method for calculating the load weight is not limited to this. For example, the density of the transport item statistically calculated from the collected sample data is stored in the input support database 25 for the transport item. The maximum load weight can be calculated by multiplying the average load rate for each transport item and the density of the transport item.

  In the above embodiment, the carbon dioxide emission is calculated from the torque and the engine speed using the engine map recorded in the emission basic unit database 15 and the emission basic unit database 27. In this case, the basic unit recorded in the engine map may be corrected using a coefficient table in which the basic unit correction coefficient corresponding to the type of engine (type of motor) is recorded. In this case, the CO2 calculating unit 116 and the CO2 emission calculating unit 214 obtain a correction coefficient based on the type of the prime mover of the essential input item, and correct the basic unit to calculate the carbon dioxide emission. Thereby, it is not necessary to prepare an engine map corresponding to all engines, and the carbon dioxide emission amount can be calculated based on a representative engine map.

  In the above embodiment, the client control unit 11 of the client terminal 10 executes a determination process as to whether or not it is a sudden start (step S7-3). In this case, the maximum value of the acceleration of the “pattern in which sudden start is suppressed” recorded in the speed pattern database 13 is used as the reference value. Moreover, the client control part 11 of the client terminal 10 performs the determination process about whether it is wavy driving | running | working (step S7-4). In this case, as the reference value, the maximum value of the acceleration energy equivalent per unit distance of the “pattern with suppressed wave running” recorded in the speed pattern database 13 is used. The reference value is not limited to these values, and it is also possible to use a statistical value (for example, an intermediate value) of a value of “a pattern that suppresses sudden start or wave driving” or “a pattern that does not suppress”. .

  ○ In the above embodiment, when it is determined that the sudden start is not suppressed (in the case of “NO” in Step S7-3), or when it is determined that the wave running is not suppressed (“NO” in Step S7-4). ”), The client control unit 11 of the client terminal 10 executes a speed pattern replacement process (step S7-5). Here, only one of them may be executed. Further, in consideration of other running conditions, a typical speed pattern considering the environmental load may be stored in the client terminal 10 and replaced with this pattern.

  Further, in the above embodiment, the speed pattern replacement unit 119e of the client control unit 11 is a speed pattern that suppresses sudden start and wave driving from the speed pattern database 13 with respect to this short trip, and the short trip distance is Extract the closest pattern. Thereby, the pattern which reduced the carbon dioxide emission amount can be utilized.

  In the above embodiment, in the short trip analysis, the server control unit 21 of the environmental load evaluation support server 20 performs a calculation process of the cumulative frequency of short trip times (step S4-1). Alternatively, the cumulative frequency of the short trip distance can be used. In this case, the short trip distance segmentation process is executed so that the relative cumulative frequency is constant (step S4-2). And the server control part 21 of the environmental load evaluation support server 20 performs the calculation process of a representative speed pattern for every short trip (step S4-3). Thereby, the travel distance in a short trip can be used as an analysis pattern variable value.

In the above embodiment, the server control unit 21 of the environmental load evaluation support server 20 executes a signal waiting time calculation process (step S2-4). Specifically, the short trip analysis means 212 of the server control unit 21 specifies the temporary stop time zone as the signal waiting time. And the short trip analysis means 212 calculates the statistical value (here, average value) of the signal waiting time for each traveling state group, and temporarily stores it in the memory. Alternatively, the signal waiting time can be calculated in consideration of the appearance frequency in the same manner as the speed pattern. In this case, the server control unit 21 calculates the cumulative frequency distribution of the suspension time. Then, the axis representing the cumulative frequency in the cumulative frequency distribution is divided into equal intervals at a constant width, and the typical stop time of each interval is specified, thereby specifying the stop time (representative stop time) having the same appearance frequency. . When performing analysis, representative stop times are sequentially set between short trips composed of representative speed patterns. Thereby, the temporary stop which considered the appearance frequency can be set in a trip, and the environmental load in this time slot | zone can be calculated.

  ○ In the above embodiment, when it is determined that the sudden start is not suppressed (in the case of “NO” in Step S7-3), or when it is determined that the wave running is not suppressed (“NO” in Step S7-4). ”), The client control unit 11 of the client terminal 10 executes a speed pattern replacement process (step S7-5). Specifically, the speed pattern replacement means 119e of the client control unit 11 uses the “speed pattern that suppresses sudden start” and the “speed pattern that suppresses wave running” from the speed pattern database 13 for this short trip. The representative speed pattern with the shortest short trip distance is extracted. Here, the “speed pattern that suppresses sudden start” and the “speed pattern that suppresses wavy driving” are not limited to the representative speed pattern, and a speed pattern that represents ideal driving can also be used. is there. In this case, data relating to the reference traveling speed is stored in the speed pattern replacing means 119e as the reference acceleration and the average traveling speed in which sudden start is suppressed. Then, the speed pattern replacement unit 119e generates a speed pattern that accelerates / decelerates at the reference acceleration, travels at a constant speed (reference travel speed), and has the same short trip distance.

(Second Embodiment)
In the first embodiment, the travel pattern is generated using the actually measured short trip. Specifically, the server control unit 21 of the environmental load evaluation support server 20 calculates an acceleration energy equivalent per unit distance (step S3-2), and executes a sort process based on the acceleration energy equivalent per unit distance (step S3-2). S3-6). Further, the server control unit 21 of the environmental load evaluation support server 20 extracts a pattern of “with suppression of wavy travel” (step S3-7), and extracts a pattern of “without suppression of wavy travel” (step S3- 8) is executed. As described above, from each group classified based on the presence / absence of the actual vehicle / empty vehicle identification flag, a traveling state group subdivided according to the presence / absence of suppression of sudden start and the presence / absence of suppression of wavelike traveling is generated.

  Instead, in the second embodiment, the short trip pattern is generalized, and the traveling pattern is generated using the generalized short trip. In order to generalize such a short trip, a running state group is generated using a frequency analysis result. Here, only a predetermined frequency range may be extracted from the measured data using a predetermined filter (for example, a bandpass filter), and the frequency analysis may be performed only for this range.

Here, it is assumed that the speed pattern of the short trip is composed of a starting part, a cruise part, and a speed reducing part, as shown in FIG. Here, the starting part is accelerating from the stop state, the cruising part is assumed to be traveling at a constant speed, and the decelerating part is decelerating from the constant speed to the stop state. It means time zone. Then, the amplitude, frequency, and delay angle of the cruising unit are calculated by frequency analysis of the speed pattern of the cruising unit, as shown in FIG. Then, statistical amplitude, frequency, and delay angle are calculated in the classification classified by the time and speed of the cruise section. Next, by superimposing the generalized frequency characteristics calculated from the frequency analysis results on the trapezoidal speed pattern consisting of the starter and decelerator, the short trip travel pattern shown in FIG. Constitute.

  A method of generating a running pattern using such frequency analysis will be described in detail below. Here, amplitude extraction processing (FIG. 21) and trip classification processing (FIGS. 22 and 23) are executed. In order to perform this processing, the server control unit 21 is further provided with frequency analysis means and trip classification means. This frequency analysis means performs frequency analysis of the cruise part of the show trip. Trip classification means classifies trips by time and distance. The trip classification means can also classify trips by “time and speed” and “speed and distance”.

(Amplitude extraction processing)
First, the amplitude extraction process will be described with reference to FIG.
Here, the server control unit 21 of the environmental load evaluation support server 20 executes a cruise unit specifying process (step S8-1). Specifically, the short trip analysis unit 212 of the server control unit 21 specifies the starting unit and the deceleration unit using a moving average calculated every predetermined time for all short trips. The starting part shall be the range where the calculated moving average value is increasing monotonically from the beginning of the short trip. The speed reduction unit shall be in the range where the calculated moving average is monotonously decreasing sequentially from the end of the short trip. Then, the section between the starting part and the deceleration part is specified as the cruise part.

  The server control unit 21 of the environmental load evaluation support server 20 executes a short trip classification process (step S8-2). Specifically, the frequency analysis means of the server control unit 21 classifies the identified cruise unit using a cruise unit classification map composed of two axes of time (cruise time) and speed (cruise speed). In this case, it is also possible to classify short trips by “time and distance” and “speed and distance”. In this embodiment, in this cruise section classification map, the cruise time axis is divided into blocks divided at intervals of 4 seconds, and the cruise speed axis is divided at intervals of 5 km / h.

And the server control part 21 of the environmental load evaluation assistance server 20 performs the following processes for every block divided by cruise time and cruise speed.
First, the server control unit 21 of the environmental load evaluation support server 20 executes a frequency analysis process for the cruise unit included in the partition block (step S8-3). Specifically, the frequency analysis means of the server control unit 21 performs frequency analysis of the short trip cruise unit included in each block. Here, the amplitude is calculated for each predetermined analysis frequency.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes representative value calculation processing (step S8-4). Specifically, the frequency analysis unit of the server control unit 21 acquires an amplitude corresponding to a preset reference value for each analysis frequency. Here, first, the first amplitude including 25% of the amplitude distribution and the second amplitude including 75% are specified for each analysis frequency. In the present embodiment, the first amplitude corresponds to “with suppression of wave running” and the second amplitude corresponds to “without suppression of wave driving”. The frequency analysis means also calculates a frequency distribution for the delay angle. In this embodiment, as for the delay angle, the statistical value (here, the median value) of the delay angle distribution of each analysis frequency is used in both cases of “with suppression of wavy travel” and “without suppression of wave travel”. . Different delay angle values may be used depending on the running state group.

  And the server control part 21 of the environmental load evaluation support server 20 performs the registration process of an analysis result (step S8-5). Specifically, the frequency analysis means of the server control unit 21 stores the representative value calculated in step S8-4 in the frequency analysis result data storage unit. In the frequency analysis result data storage unit, the frequency distribution of the first amplitude, the second amplitude, and the delay angle is recorded for each block divided by the cruise time and the cruise speed.

(Trip classification process)
Next, the trip classification process will be described with reference to FIGS.
Here, the server control unit 21 of the environmental load evaluation support server 20 executes a trip block classification process (step S9-1). Specifically, the trip classifying means of the server control unit 21 classifies the blocks into blocks divided by trip time and trip distance. In this embodiment, as shown in FIG. 23, the trip classification map using the trip time on the horizontal axis and the trip distance on the vertical axis is divided into blocks divided at predetermined intervals. Here, a block adjacent to the average speed line is divided so as to be fine with a line indicating the average speed (average speed line) as a center. In this trip classification map, the traveling state due to traffic jams is reflected in each trip. That is, when the trip distance is long with respect to the trip time, a smooth running state is shown. On the other hand, when the trip distance is short with respect to the trip time, it indicates that smooth running was not possible due to traffic jams or the like.

And the server control part 21 of the environmental load evaluation support server 20 performs the following processes for every block divided by trip time and trip distance.
First, the server control unit 21 of the environmental load evaluation support server 20 executes an analysis process of the appearance frequency of the short trip distance (step S9-2). Specifically, the short trip analysis unit 212 of the server control unit 21 calculates the cumulative frequency of the short trip distance and identifies typical short trips in which the appearance frequency of each short trip is equal, similarly to step S2-6. To do. Then, the short trip analysis unit 212 divides the appearance frequency into a predetermined number of sections, and specifies the median short trip distance of each divided section.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes an analysis process of the appearance frequency of the short trip time (step S9-3). Specifically, the short trip analysis unit 212 of the server control unit 21 calculates a cumulative frequency of short trip times, and identifies typical short trips having the same appearance frequency of each short trip. Then, the short trip analysis unit 212 divides the appearance frequency into a predetermined number of sections, and specifies the short trip time of the median value of each divided section.

  Next, the server control unit 21 of the environmental load evaluation support server 20 executes an analysis process of the appearance frequency of the stop time (step S9-4). Specifically, the short trip analysis unit 212 of the server control unit 21 calculates a cumulative frequency of stop times, and identifies typical stop times with the same appearance frequency of each stop time. Then, the short trip analysis unit 212 divides the appearance frequency into a predetermined number of sections, and specifies the stop time of the median value of each divided section.

  Then, the server control unit 21 of the environmental load evaluation support server 20 executes a short trip reconfiguration process (step S9-5). Specifically, the trip classification unit of the server control unit 21 generates a start unit and a deceleration unit using typical accelerations of various traveling state groups. At this stage, the trip generation means acquires the short trip distance specified in step S9-2, the short trip time specified in step S9-3, and the acceleration and deceleration of the starter and the deceleration unit. The acceleration / deceleration unit calculates the statistical value of the short trip recorded in the sample database 22 according to the running state group. Then, the following simultaneous equations are generated using the cruise time, the cruise speed, the time of the start unit (acceleration time) and the time of the deceleration unit (deceleration time) as variables.

[Short trip time] = [Acceleration time] + [Cruise time] + [Deceleration time]
[Cruising speed] = [acceleration] * [acceleration time] = [deceleration] * [deceleration time]
[Short trip distance] = [cruising speed] * [cruising time] + ([acceleration] * [acceleration time] ^ 2) / 2 + ([deceleration] * [deceleration time] ^ 2) / 2
By solving these simultaneous equations, a trapezoidal speed pattern consisting of a starter, a cruiser, and a speed reducer is generated.

  And a trip production | generation means acquires the frequency distribution of the 1st amplitude, 2nd amplitude, and delay angle corresponding to the calculated cruise time and cruise speed from a frequency analysis result data storage part. Then, a representative traveling pattern of “with suppression of wavy travel” using the first amplitude and “without suppression of wavy travel” using the second amplitude is generated.

According to this embodiment, the following effects can be obtained.
In the above embodiment, the frequency analysis result for the short trip is calculated in the amplitude extraction process. Then, in the trip classification process, the short trip is reconfigured using the frequency analysis result, and the representative travel pattern is generated using the short trip. When wavy running is performed, the speed fluctuation is large, and the amplitude becomes large in the frequency analysis. As described above, since the running state can be represented by the frequency and the amplitude, a typical representative running pattern can be generated using the frequency analysis result.

In addition, you may change each said embodiment as follows.
In the above embodiment, frequency analysis is performed in the cruise section. The section in which the frequency analysis is performed is not limited to the cruise section, and the frequency analysis may be performed in the start section and the deceleration section. Using the frequency and amplitude calculated by this frequency analysis, it is also possible to reconfigure the starting unit, the cruise unit, and the deceleration unit for each traveling state group, and generate a traveling pattern.

  In the above embodiment, frequency analysis is used to generate a representative travel pattern. Alternatively, frequency analysis can be used to evaluate actually measured travel data. In this case, the server control unit 21 of the environmental load evaluation support server 20 acquires actually measured trip data and develops this trip into a short trip. Then, the server control unit 21 identifies the deployed short trip cruise unit and performs frequency analysis on the cruise unit. And the server control part 21 evaluates a driving | running | working state with the frequency distribution of the amplitude calculated by the frequency analysis. That is, when the amplitude is large, it is possible to propose an operation that reduces the environmental load by reducing the amplitude. Note that this evaluation is not limited to the evaluation of the cruise section, but frequency analysis is performed on the start section and the deceleration section, and the traveling state is evaluated based on the frequency distribution of the calculated amplitude. Good.

  In the above embodiment, the traveling state of the cruising unit is reconfigured using the amplitude specified using a predetermined reference value (25%, 75%). Instead of this, the driving pattern may be reconfigured by determining the amplitude for each predetermined frequency range in accordance with the driving state and road conditions. In this case, the environmental load evaluation support server 20 is provided with an evaluation target frequency data storage unit for determining a frequency region for performing frequency analysis in association with information (traveling state group) for specifying the traveling state and road condition. And according to the designated driving | running | working state group, a frequency range is determined using an evaluation object frequency data memory | storage part, and a frequency analysis is performed. For example, when a sufficient inter-vehicle distance is ensured or when the speed is changed slowly according to the traffic signal change, the amplitude of the frequency range corresponding to this change is reduced, and the environmental load is taken into account. Can be evaluated as driving.

DESCRIPTION OF SYMBOLS 10 ... Client terminal, 11 ... Client control part, 11a ... Input control means, 11b ... Calculation control means, 111 ... Simple input means, 112 ... Option input means, 113 ... Default value setting means, 114 ... Speed pattern estimation means, 115 ... vehicle speed conversion means, 116 ... CO2 calculation means, 117 ... output control means, 118 ... digital data input means, 119 ... reduction support means, 12 ... input support database, 13 ... speed pattern database, 14 ... conversion coefficient database, 15 ... Emission basic unit database, 20 ... Environmental load evaluation support server, 21 ... Server control unit, 211 ... Short trip developing means, 212 ... Short trip analyzing means, 213 ... Representative travel pattern calculating means, 214 ... CO2 emission calculating means, 215 ... Program distribution means, 22 ... Sun Le database, 23 ... speed pattern database 24 ... representative driving pattern database, 25 ... input support database, 26 ... transform coefficient database, 27 ... emissions per unit database 28 ... evaluation program data storage unit.

Claims (11)

Operation record data storage means for recording a travel history about the travel speed during operation;
Corresponding to the running state group, speed pattern data storage means for recording a representative speed pattern for each representative analysis pattern variable value;
An environmental load evaluation support system comprising a control means for calculating the amount of carbon dioxide emitted based on the running speed,
The control means is
The trip constituting the travel history recorded in the operation record data storage means is expanded into a short trip delimited in a pause state where the travel speed is “0”,
For each short trip, calculate an analysis pattern variable value representing the size of each short trip,
For the travel history recorded in the operation record data storage means, calculate the cumulative frequency distribution of the analysis pattern variable value,
In the cumulative frequency distribution, the axis representing the cumulative frequency is divided into equal intervals with a constant width, and each short trip corresponding to the representative analysis pattern variable value composed of the statistical value of each interval is specified as a representative speed pattern having the same appearance frequency. An environmental load evaluation support system which records in the speed pattern data storage means corresponding to each traveling state group of each short trip, and calculates carbon dioxide emission using this representative speed pattern.   When the control means acquires an evaluation target in which the magnitude of a trip is specified, a representative analysis pattern variable of a representative speed pattern until the evaluation target trip size is reached in correspondence with a traveling state group. The environmental load evaluation support system according to claim 1, wherein values are sequentially combined, and evaluation is performed using a carbon dioxide emission amount corresponding to the representative speed pattern. The control means performs frequency analysis in each short trip, calculates the frequency distribution of the amplitude,
Calculate the statistical value of the frequency distribution of the amplitude corresponding to the running state group,
Using the statistics of the frequency distribution of the amplitude, reconstruct the short trip,
The environmental load evaluation support system according to claim 1, wherein a representative speed pattern is generated using the reconfigured short trip. When the control means obtains an evaluation object in which a travel history about the travel speed during operation is recorded, the amount of carbon dioxide discharged based on the travel speed is calculated,
The trip constituting the travel history is expanded into a short trip separated by a pause state where the travel speed becomes “0”,
For each short trip, in the speed pattern data storage means, a representative speed pattern with a small amount of carbon dioxide emission is identified in correspondence with the running state group,
The environmental load evaluation support system according to any one of claims 1 to 3, wherein the carbon dioxide emission when the representative speed pattern is replaced is output as a comparison result. The control means calculates the acceleration at the start of each short trip,
5. The environmental load evaluation support system according to claim 4, wherein a short trip with the acceleration equal to or higher than a reference value is replaced with a representative speed pattern with a small amount of carbon dioxide emission. The control means calculates an acceleration energy equivalent per unit distance in each short trip,
6. The environmental load evaluation support system according to claim 4, wherein a short trip having an acceleration energy equivalent of a reference value or more is replaced with a representative speed pattern with a small amount of carbon dioxide emission. The control means calculates a time interval between short trips,
The environmental load evaluation support system according to any one of claims 4 to 6, wherein a replacement is made with a speed pattern when idling is stopped between short trips in which the time interval is equal to or greater than a reference time. .   The environmental load evaluation support system according to any one of claims 1 to 7, wherein a time required for a short trip is used as the analysis pattern variable value.   The environmental load evaluation support system according to any one of claims 1 to 7, wherein a travel distance in a short trip is used as the analysis pattern variable value. Operation record data storage means for recording a travel history about the travel speed during operation;
Corresponding to the running state group, speed pattern data storage means for recording a representative speed pattern for each representative analysis pattern variable value;
A method for supporting the evaluation of environmental load using an environmental load evaluation support system comprising a control means for calculating the amount of carbon dioxide emitted based on the traveling speed,
The control means is
The trip constituting the travel history recorded in the operation record data storage means is expanded into a short trip delimited in a pause state where the travel speed is “0”,
For each short trip, calculate an analysis pattern variable value representing the size of each short trip,
For the travel history recorded in the operation record data storage means, calculate the cumulative frequency distribution of the analysis pattern variable value,
In the cumulative frequency distribution, the axis representing the cumulative frequency is divided into equal intervals with a constant width, and each short trip corresponding to the representative analysis pattern variable value composed of the statistical value of each interval is specified as a representative speed pattern having the same appearance frequency. An environmental load evaluation support method comprising: recording in the speed pattern data storage means corresponding to each short trip traveling state group, and calculating a carbon dioxide emission amount using the representative speed pattern. Operation record data storage means for recording a travel history about the travel speed during operation;
Corresponding to the running state group, speed pattern data storage means for recording a representative speed pattern for each representative analysis pattern variable value;
A program for supporting the evaluation of environmental load using an environmental load evaluation support system comprising a control means for calculating the amount of carbon dioxide emitted based on the running speed,
The control means;
The trip constituting the travel history recorded in the operation record data storage means is expanded into a short trip delimited in a pause state where the travel speed is “0”,
For each short trip, calculate an analysis pattern variable value representing the size of each short trip,
For the travel history recorded in the operation record data storage means, calculate the cumulative frequency distribution of the analysis pattern variable value,
In the cumulative frequency distribution, the axis representing the cumulative frequency is divided into equal intervals with a constant width, and each short trip corresponding to the representative analysis pattern variable value composed of the statistical value of each interval is specified as a representative speed pattern having the same appearance frequency. An environmental load evaluation support program that records in the speed pattern data storage means in correspondence with each short trip traveling state group and functions as means for calculating carbon dioxide emission using this representative speed pattern .

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