JP2011121417A - Travel control system, control program, and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a traveling control system which attains compatibility between safe traveling control to avoid the collision of a self-vehicle with the preceding vehicle and traveling control to achieve a comfortable ride in such a manner that any rapid speed change is not caused in the self-vehicle. <P>SOLUTION: The traveling control system is configured to set a plurality of prediction sections by dividing an arrival time until the self-vehicle reaches the location of the preceding vehicle at the current time (step S105), and to calculate the target acceleration of the self-vehicle on the elapsed time of the arrival time for every prediction section (step S107), and to create an evaluation function with the prediction acceleration of the self-vehicle in each prediction section or operation variation in two continuous prediction sections as an input value (step S108), and to acquire the acceleration of the self-vehicle in each prediction section based on generalized prediction control to obtain the input value to minimize the output value of the evaluation function (step S109), and to control the acceleration of the self-vehicle following the current time to the acquired value (step S110). <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a travel control system, a control program, and a recording medium recording the same.

  In recent years, research and development on ITS (Intelligent Transport Systems) technology has been conducted to solve environmental problems caused by traffic accidents, traffic jams, and exhaust gas from automobiles. An ACC (Adaptive Cruise Control) system that controls traveling when following a preceding vehicle has been proposed for the purpose of improving fuel efficiency and reducing driver's driving load. At present, the ACC system has been put into practical use in some vehicles, and has attracted attention as a system that will become standard equipment in the future.

  As an example of this ACC system, Patent Document 1 discloses a control device that controls the host vehicle speed based on the inter-vehicle distance from a preceding vehicle. This control device detects whether or not there is a preceding vehicle within the safe inter-vehicle distance calculated from the current vehicle speed at the current time, and when there is a preceding vehicle, the inter-vehicle distance with the preceding vehicle becomes the safe inter-vehicle distance. When there is no preceding vehicle, the own vehicle speed is controlled to be the set vehicle speed.

  Also, the target vehicle speed of the host vehicle is calculated using the inter-vehicle distance from the preceding vehicle and the vehicle speed / acceleration of the host vehicle, and the deviation between the target vehicle speed and the host vehicle speed is reduced to make the two coincide. Techniques for performing control have been proposed.

  As an example of a device that performs this feedback control, Patent Document 2 discloses a control device that stores data such as the inter-vehicle distance from the preceding vehicle and the vehicle speed and acceleration of the host vehicle at regular time intervals. In this control device, data stored within a predetermined time before the current time is input to the neural network, and on the basis of the output value of the neural network, the throttle opening and the brake operation necessary to bring the vehicle speed close to the target speed. A quantity etc. are set.

  In Patent Document 3, the vehicle speed and acceleration at the current time are used to predict the vehicle speed in one time zone immediately after the current time, and the vehicle speed is used to estimate the vehicle speed between the preceding vehicle after the time zone has elapsed. Discloses a control device for calculating a safe inter-vehicle distance to be secured. In this control device, apart from the safe inter-vehicle distance, the inter-vehicle distance after the passage of the time zone is predicted based on the inter-vehicle distance at the current time, and based on the difference between the inter-vehicle distance and the safe inter-vehicle distance, A target speed in the belt is calculated.

  Patent Document 4 discloses a control device in which feed-forward control is used in combination with the above-described feedback control. The feedforward control in this control device calculates the change rate of the current target vehicle speed from the target vehicle speed at the previous sampling and the target vehicle speed at the current sampling, and the calculated change rate of the target vehicle speed continues at the next sampling. The target vehicle speed after a predetermined time has elapsed is set.

JP 60-215432 A JP-A-4-71933 JP-A-5-104977 JP-A-8-40231

  However, in Patent Document 1, when the preceding vehicle changes the lane from the lane of the host vehicle to the adjacent lane, the vehicle speed control based on the safe inter-vehicle distance is switched to the vehicle speed control based on the set vehicle speed. For this reason, a rapid speed change may occur, which may cause the driver to feel uncomfortable riding.

  Further, in Patent Document 2, there are various types of data input to the neural network, such as the vehicle speed / acceleration and inter-vehicle distance of the host vehicle. For each of these data, data stored within a predetermined time before the current time is stored. Entered. As a result, the amount of data processed by the neural network becomes enormous, which may cause a delay in the control system and prevent the vehicle from being quickly controlled.

  Moreover, in patent document 3, the time delay of a response and an overshoot may arise by running control by the one-step prediction which estimates the target speed in one time slot | zone immediately after the present time. In addition, since the vehicle speed at the time zone has been predicted under the condition that the vehicle speed and acceleration at the current time are maintained, the vehicle changes the vehicle speed and acceleration within the time zone. There may be a large gap between the predicted vehicle speed and the actual vehicle speed. From the above points, there is a possibility that sufficient control performance cannot be obtained.

  Further, in Patent Document 4, since the estimation error is not considered in the rate of change of the target vehicle speed, there is a limit to predicting the target vehicle speed with high accuracy.

  The present invention has been made in view of such a situation, and an object of the present invention is to record a travel control system mounted on a moving body where a travel operation is performed, a control program for controlling the travel control system, and a control program. A safe traveling control that can avoid a rear-end collision with a preceding object traveling in front of the moving body, and a comfortable traveling control that does not cause a sudden speed change in the moving body In addition, the long-term acceleration can be predicted, so that sufficient control performance can be obtained. In addition, the target time for acceleration can be determined by the distance between the moving object and the preceding object, and the moving object. A travel control system, a control program, and a recording medium that can achieve both improvement in control performance accuracy and reduction in the amount of calculation required for control by variably setting according to the speed of the vehicle. It is to be.

  A travel control system according to a first aspect of the present invention is a travel control system that is mounted on a mobile object on which a travel operation is performed, the mobile object at a current time and a preceding object that travels in front of the mobile object, The arrival time calculating means for calculating the arrival time until the moving body reaches the position of the preceding object at the current time by dividing the distance between the two by the speed of the moving body at the current time; By dividing the time at predetermined time intervals, a prediction interval setting unit that sets a plurality of prediction intervals that are prediction target times of acceleration, and at the time when the arrival time has elapsed, the speed of the moving object is set to The distance between the moving body and the preceding object can be made closer to the speed, and can be brought closer to a safe distance that is larger than the sum of the free running distance and the braking distance calculated based on the speed of the moving body at the current time. Above Target acceleration calculation means for calculating the target acceleration of the moving body for each prediction section, the predicted acceleration of the mobile body in each prediction section, and the operation change to the moving body between two consecutive prediction sections When an amount is input, an evaluation function generation that generates an evaluation function that adds and outputs the cumulative value related to the difference between the target acceleration and the predicted acceleration in each prediction interval and the cumulative value related to each operation change amount is output. And an acceleration of the mobile body in each prediction section based on generalized predictive control for obtaining an input value that minimizes an output value of the evaluation function, and the mobile body after the current time is obtained as the acquired value And an acceleration control means for controlling the acceleration.

  Preferably, the target acceleration in each prediction interval is a predetermined weighting factor to a value obtained by dividing the difference between the distance between the moving object and the preceding object at the current time and the safety distance by the arrival time. It is calculated by adding the relative speed between the moving object and the preceding object at the current time to the multiplied value, and dividing the added value by the arrival time.

  Further preferably, the cumulative value related to the difference between the target acceleration and the predicted acceleration in each predicted section is a value obtained by summing the square values of the differences between the target acceleration and the predicted acceleration in each predicted section. The cumulative value related to the quantity is a value obtained by summing a value obtained by multiplying a square value of the operation change amount of the input value in two consecutive prediction intervals by a predetermined weighting coefficient.

  Preferably, the apparatus further includes a dynamic model creating unit that creates a dynamic model indicating a relationship between a force acting on the moving body and an acceleration of the moving body, and the acceleration control unit uses the dynamic model to The acceleration of the moving body in a prediction section is acquired.

  Further preferably, based on the dynamic model created by the dynamic model creating means, a linear model creation for creating a linear model in which the relationship between the speed of the moving body and the force acting on the moving body is linearly expressed The acceleration control means calculates a force acting on the moving body corresponding to an input value that minimizes an output value of the evaluation function, using the linear model; The acceleration of the moving body in each prediction interval is acquired by inputting an acting force into the dynamic model.

  A control program according to a second aspect of the present invention is a control program for controlling a travel control system mounted on a mobile body on which a travel operation is performed, the mobile program at the current time and the front of the mobile body The arrival time for calculating the arrival time until the moving body reaches the position of the preceding object at the current time by dividing the distance from the preceding object traveling on the vehicle by the speed of the moving body at the current time A calculation procedure, a prediction interval setting procedure for setting a plurality of prediction intervals that are prediction target times of acceleration by dividing the arrival time at predetermined time intervals, and at the time when the arrival time has elapsed, The speed is brought close to the speed of the preceding object, and the distance between the moving object and the preceding object is set to be larger than the total of the free running distance and the braking distance calculated based on the speed of the moving object at the current time. Big A target acceleration calculation procedure for calculating the target acceleration of the mobile body that can be close to a safe distance for each prediction section, the predicted acceleration of the mobile body in each prediction section, and the two consecutive prediction sections When the operation change amount to the moving body at is input, the cumulative value related to the difference between the target acceleration and the predicted acceleration in each prediction section and the cumulative value related to each operation change amount are added and output. Based on the evaluation function generation procedure for generating the evaluation function and the generalized prediction control for obtaining the input value that minimizes the output value of the evaluation function, the acceleration of the moving body in each prediction section is acquired, and the acquired value And causing the travel control system to execute an acceleration control procedure for controlling acceleration of the moving body after the current time.

  A recording medium according to the third aspect of the present invention is a computer-readable recording medium that records the control program.

  According to the present invention, the acceleration of the moving body after the current time is controlled to the acceleration acquired based on the generalized predictive control by the evaluation function, thereby bringing the speed of the moving body close to the speed of the preceding object, It is possible to ensure a distance between the moving body and the preceding object that is greater than the sum of the free running distance and the braking distance calculated based on the speed at the current time. As a result, safe traveling control that can avoid a rear-end collision with a preceding object can be realized. Further, according to the above-described acceleration control, the operation change amount to the moving body becomes small in each time zone after the current time corresponding to each prediction section, so that the operation amount to the moving body becomes almost constant. can do. As a result, it is possible to realize traveling control with good riding comfort without causing a rapid speed change in the moving body.

  In generalized prediction control using an evaluation function, acceleration prediction is multistage prediction performed in a plurality of prediction sections after the current time, and thus long-term acceleration prediction is possible. Thereby, control performance improves.

  In addition, when the moving body is traveling at a high speed, traveling control is performed to bring the distance between the moving body and the preceding object closer to the safe distance calculated based on the speed of the moving body at the current time. When the distance between the object and the moving object is traveling at a low speed, the distance between the object and the preceding object is shortened. Thus, the distance between the moving body and the preceding object is adjusted according to the speed of the moving body.

  In addition, the arrival time until the moving body reaches the position of the preceding object at the current time is calculated, and divided into time intervals, thereby setting a plurality of prediction sections as acceleration prediction target times. Thereby, since the prediction section used as the acceleration prediction target time is variably set according to the arrival time, the accuracy of the control performance is improved as compared with the case where the prediction section is made constant. Further, as the speed of the moving body increases, the safety distance increases. Thereby, at the time of high-speed traveling of a mobile body, arrival time becomes long and the number of prediction sections becomes large. As a result, since the acceleration is predicted for a long time, smooth running control is performed. In addition, as the speed of the moving body decreases, the safety distance decreases. As a result, when the moving body travels at a low speed, the arrival time is shortened, so that the number of prediction sections is reduced, and the amount of calculation required for control is reduced. As a result, variable control according to the reach distance and the speed of the moving body can be realized.

It is a block diagram which shows the structure of the traveling control system in embodiment of this invention. It is the schematic which shows the positional relationship of the own vehicle by which a traveling control system is mounted, and the preceding vehicle which drive | works the front of the own vehicle. It is a flowchart which shows the process of a traveling control system. It is the schematic which shows the acceleration prediction object time by a traveling control system. It is a figure which shows the relationship between the speed of the own vehicle in the present time, and a safe distance. It is a flowchart which shows the detail of the process of step S104 of FIG. It is a figure which shows the relationship between the own vehicle and preceding vehicle speed and time in the simulation of the 1st run pattern. It is a figure which shows the relationship between the inter-vehicle distance and safe distance, and time in the simulation of a 1st driving | running pattern. It is a figure which shows the relationship between the own vehicle and preceding vehicle speed and time in the simulation of a 2nd driving | running pattern. It is a figure which shows the relationship between the distance between vehicles, safety distance, and time in the simulation of a 2nd driving | running pattern. It is a figure which shows the relationship between the own vehicle and preceding vehicle speed and time in the simulation of the 3rd run pattern. It is a figure which shows the relationship between the distance between vehicles, safety distance, and time in the simulation of the 3rd run pattern.

  Hereinafter, a travel control system 1 according to an embodiment of the present invention will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals, and description thereof will not be repeated. The traveling control system 1 is mounted on a moving body that performs a traveling operation. Hereinafter, a case where the traveling control system 1 is mounted on an automobile as the moving body will be described as an example.

  FIG. 1 shows the configuration of the travel control system 1, and FIG. 2 shows the positions of a host vehicle 2 that is a car on which the travel control system 1 is mounted and a preceding vehicle 3 that is a car that travels ahead of the host vehicle 2. Showing the relationship.

  As shown in FIG. 1, the travel control system 1 includes a host vehicle measurement sensor 10, a preceding vehicle measurement sensor 11, and a control device 12.

The own vehicle measurement sensor 10 is composed of, for example, a sensor that optically detects the rotation of the drive shaft of the own vehicle 2 and measures the speed v _a (t _n ) of the own vehicle 2 at the current time t _n. .

Preceding vehicle measuring sensor 11, for example, is composed of a millimeter-wave radar and a laser radar, vehicle distance d (t _n) and between the own vehicle 2 and the preceding vehicle 3 at the present time t _n, the current time t rate of the _n preceding vehicle 3 v measuring _b a (t _n).

  The control device 12 includes a storage unit 20, a control unit 21, and an interface 22.

  The storage unit 20 includes a ROM (Read Only Memory), a RAM (Random Access Memory), a hard disk device, and the like. The storage unit 20 stores a program, input data, and the like, and functions as a work area of the control unit 21.

  The control unit 21 includes a CPU (Central Processing Unit) and executes a program stored in the storage unit 20.

  The interface 22 is connected to the own vehicle measurement sensor 10 and the preceding vehicle measurement sensor 11, and the throttle actuator 30 and the brake actuator 31 installed in the own vehicle 2.

  The control device 12 having the above configuration receives data from the own vehicle measurement sensor 10 and the preceding vehicle measurement sensor 11 through the interface 22, and calculates the calculation result of the control unit 21 from the throttle actuator 30 and the brake actuator. By outputting to 31, the traveling control according to the calculation result is made possible.

  FIG. 3 is a flowchart showing the processing of the traveling control system 1, and FIG. 4 shows the acceleration prediction target time by the traveling control system 1. The process performed with the traveling control system 1 is demonstrated using FIGS. Note that the algorithm shown in the flowchart of FIG. 3 is stored as a program in the storage unit 20 (see FIG. 1) of the control device 12. For example, when the user operates a switch provided in the vehicle interior, the travel control is performed. This is executed by the control unit 21 (see FIG. 1) in response to the system 1 being turned on.

First, a dynamic model of the host vehicle 2 of Formula 1 showing the relationship between the force u acting on the host vehicle 2 and the acceleration dv _a / dt of the host vehicle 2 is created (step S101).

The force u acting on the host vehicle 2 is an input value and is an air resistance μ proportional to the force mdv _a / dt required for acceleration of the host vehicle 2 and the square value v _a ² of the speed v _a of the host vehicle 2. _l It corresponds to the sum of Av _a ² and rolling resistance μ _r W proportional to the weight W of the host vehicle 2 (the value obtained by multiplying the mass m of the host vehicle 2 by the gravitational acceleration). The mass m, the air resistance coefficient μ _l , the front projection area A, the rolling resistance coefficient μ _r , and the weight W of the host vehicle 2 are stored in advance in the storage unit 20 (see FIG. 1) of the control device 12. The

Then, during the vehicle sensors for measurement 10 and the preceding vehicle measuring sensor 11, the current time t _n of the own speed of the vehicle 2 v _a (t _n), the host vehicle 2 and the preceding vehicle 3 at the current time t _n inter-vehicle distance d (t _n), acquires the preceding vehicle 3 speed v _b (t _n) of the current time t _n, the vehicle 2 and the preceding vehicle third velocity _{v a (t n), v} b (t _n ), the relative speed v _ab (t _n ) between the host vehicle 2 and the preceding vehicle 3 is acquired (step S102).

Next, an arrival time T _c (t _n ) (see FIG. 2) until the host vehicle 2 reaches the position of the preceding vehicle 3 at the current time t _n is calculated (step S103). In this step S103, the arrival time T _c (t _n ) is obtained by _{dividing the} inter-vehicle distance d (t _n ) acquired in step S102 by the speed v _a (t _n ) of the host vehicle 2 at the current time t _n. Is calculated.

  Next, the dynamic model created in step S101 is converted into a linear model (step S104). This process is performed to reduce the calculation load, and will be described in detail later.

Next, a plurality of prediction intervals N (t _n ) (see FIG. 4) are set by dividing the arrival time T _c (t _n ) calculated in step S103 by a predetermined time interval T (step 4). S105). Each prediction section N (t _n ) is an acceleration prediction target time, and the speed v _a (t _n ) of the host vehicle 2 at the current time t _n and the inter-vehicle distance d ( t _n ) and the time interval T are used to calculate according to Equation 2.

In the expression _{2, d (t n) /} v a (t n) corresponds to the arrival time T _c which is calculated in step S103 (t _n). The time interval T is stored in advance in the storage unit 20 (see FIG. 1) of the control device 12.

Next, using the speed v _a (t _n ) of the host vehicle 2 at the current time t _n , _a safety distance _dr (t _n ) to be secured between the host vehicle 2 and the preceding vehicle 3 (see FIG. 2). Is calculated by Equation 3 (step S106).

The safe distance d _r (t _n ) is calculated based on the speed v _a (t _n ) at the current time t _{n and} the free running distance v _a (t _n ) t _r and the braking distance v _a (t _n ) ² / 2μg It is a value larger than the total value. Specifically, the safety distance d _r (t _n) is added and the sky run distance _{v a (t n) t r} , and the braking distance ^{_{v a (t n) 2 /}} 2μg, and stopping when the vehicle-to-vehicle distance d _min It is a combined value. In the case where the safety distance d _r (t _n ) is ensured, the host vehicle 2 is braked after the brake is applied, and then the host vehicle 2 is free running distance v _a (t _n ) t _r and the braking distance v _a (t It travels a distance which is the sum of the _n) ^2/2 [mu] g when stopped, the own vehicle 2 becomes away from the at least stopped vehicle distance d _min as the preceding vehicle 3. The stop-to-vehicle distance d _min is a desirable inter-vehicle distance at the time of stop, and is set in advance as a parameter. Further, the stop-to-vehicle distance d _min , the static friction coefficient μ, and the gravitational acceleration g used in Expression 3 are stored in advance in the storage unit 20 (see FIG. 1) of the control device 12.

FIG. 5 shows the relationship between the speed v _a (t _n ) of the host vehicle 2 at the current time t _n and the safe distance d _r (t _n ). As shown in FIG. 5, the safe distance d _r (t _n ) tends to be calculated longer as the speed v _a (t _n ) increases. Also, when the road surface is wet (static friction coefficient μ = 0.5), the static friction coefficient μ is smaller than when the road surface is dry (static friction coefficient μ = 0.7). _r (t _n ) tends to be calculated longer.

Then, after the execution of step S106 in FIG. 3, the target acceleration w (t _n + j) (see FIG. 4) of the host vehicle 2 is calculated for each prediction section N (t _n ) (step S107). The target acceleration w (t _n + j) is determined by controlling the acceleration of each prediction section N (t _n ) to this value, so that the speed v of the host vehicle 2 at the time point when the arrival time T _c (t _n ) has elapsed. _a can be approximated to the speed v _b of the preceding vehicle 3, and the inter-vehicle distance d between the host vehicle 2 and the preceding vehicle 3 can be approximated to the safety distance d _r (t _n ). Is done.

According to Equation 4, the difference between the inter-vehicle distance d (t _n ) and the safe distance d _r (t _n ) at the current time t _n is calculated as the arrival time T _c (t _n ) (in Equation 4, N (t _n ) T The relative speed v _ab (t _n ) at the current time t _n acquired in step S102 is added to the value obtained by multiplying the value divided by the predetermined weighting coefficient γ, and the added value is reached. By dividing by time T _c (t _n ) (corresponding to N (t _n ) T in Equation 4), the target acceleration w (t _n + j) is calculated. The weighting coefficient γ is stored in advance in the storage unit 20 of the control device 12.

Next, the evaluation function J (t _n ) shown in Expression 5 is generated (Step S108).

The evaluation function J (t _n ) is a deviation between the target acceleration w (t _n + j) and the predicted acceleration y _p (t _n + j) of the host vehicle 2 (see FIG. 4) in each prediction interval N (t _n ). , An accelerator or brake operation change amount Δu (t _n + j−1) (see FIG. 4) occurring between two consecutive prediction intervals N (t _n ) is taken into consideration.

The predicted acceleration y _p (t _n + j) is the predicted acceleration of the host vehicle 2 from the current time t _n to j time (time in units of the time interval T), and within each predicted section N (t _n ) , Given as a constant value. For example, y _p (t _n +2) shown in FIG. 4 is the predicted acceleration in the prediction interval 2.

The operation variation _{Δu (t n + j-1} ) is an operation amount of change that occurs between the j-2 time destination current time t _n, to j-1 times the destination of the current time t _n, later Δu (t _n + j−1) = u (t _n + j−1) −u (t _n + j−2). For example, Δu (t _n +2) shown in FIG. 4 is an operation change amount that occurs when time moves from section 2 to section 3, and Δu (t _n +2) = u (t _n +2) − u (t _n +1).

Here, an outline of the generalized predictive control for calculating the operation change amount Δu (t _n + j−1) will be described.

First, the generalized predictive control model is expressed by Equation 6. In Equation 6, q ⁻¹ represents an operator that is delayed by one time. Further, A (q ⁻¹ ) and B (q ⁻¹ ) in Expression 6 are expressed by Expression 7.

Then, E _j (q ⁻¹ ) and F _j (q ⁻¹ ) satisfying the relationship of Expression 8 are obtained. In Equation 8, Δ = 1−q ⁻¹ .

Here, E _j (q ⁻¹ ) and F _j (q ⁻¹ ) can be obtained by solving Equation 8 numerically, but must be calculated every time j changes. Therefore, the Diophantine equation is used recursively to reduce the amount of calculation. Specifically, as shown in Expression 9, B (q ⁻¹ ) E _j (q ⁻¹ ) is set as G _j (q ⁻¹ ), and the calculation shown in Expression 10 is performed.

Next, the free response term h _{k + 1} is expressed by Equation 11. Each element h _{k + j} shown in Expression 11 is obtained by Expression 12.

Next, the elements of the matrix G, which is a step response, are expressed by Equation 13.

An operation change amount (corresponding to Δu (k) in Expression 14) that minimizes the output value of the evaluation function J (t _n ) is calculated by Expression 14 to which Expressions 12 and 13 are applied.

Then, in the evaluation function J (t _n ) of Equation 5, the cumulative value (the cumulative value regarding the difference between the target acceleration w (t _n + j) and the predicted acceleration y _p (t _n + j) in each prediction interval N (t _n ) The calculated value of the first term) and the cumulative value (calculated value of the second term) related to the operation change amount Δu (t _n + j−1) are added and output.

More specifically, the calculated value of the first term is the square value of the difference between the target acceleration w (t _n + j) and the predicted acceleration y _p (t _n + j) in each prediction interval N (t _n ). The calculated value of the second term is a square value of the operation change amount Δu (t _n + j−1) in two consecutive prediction intervals N (t _n ), and a predetermined weighting coefficient λ _j A value obtained by adding the calculated values of the first and second terms is output. The weighting coefficient λ _j is stored in advance in the storage unit 20 of the control device 12.

This evaluation function J (t _n ) is when the difference between the target acceleration w (t _n + j) and the predicted acceleration y _p (t _n + j) or the operation change Δu (t _n + j-1) is small. Has a feature that the output value decreases as the calculated values of the first and second terms decrease.

Further, the evaluation function J (t _n ) has a characteristic that a value that becomes dominant with respect to the output value is changed by changing the value of the weighting coefficient λ _j . That is, when the weighting coefficient λ _j is small, the cumulative value (calculated value of the first term) regarding the difference between the target acceleration w (t _n + j) and the predicted acceleration y _p (t _n + j) becomes dominant, and the weighting is performed. When the coefficient λ _j is large, the cumulative value (calculated value of the second term) regarding the operation change amount Δu (t _n + j−1) becomes dominant.

Then, after the execution of step S108 in FIG. 3, the acceleration of the host vehicle 2 in each prediction section N (t _n ) based on generalized prediction control for obtaining an input value that minimizes the output value of the evaluation function J (t _n ). a (t _n + j) (see FIG. 4) is acquired (step S109).

Note that step S109 is executed using the linear model created in step S104. As a result, the difference from the target acceleration w (t _n + j) is small, and the operation change amount Δu (t _n + j The acceleration a (t _n + j) that decreases -1) is acquired for each prediction interval N (t _n ).

Incidentally, in the case of setting the evaluation function J (t _n) of weighting coefficients lambda _j (see Equation 5) smaller, the target acceleration w (t _n + j) to close trend large acceleration a (t _n + j) is If the weighting coefficient λ _j of the evaluation function J (t _n ) is set large, the acceleration a (t _n + j) that tends to decrease the operation change amount Δu (t _n + j-1) Is acquired.

After execution of step S109 in FIG. 3, the acceleration a (t _n + j) acquired in step S109 is output to the throttle actuator 30 and the brake actuator 31 through the interface 22 (see FIG. 1) (step S110). ). As a result, the acceleration of the host vehicle 2 after the current time t _n is controlled to the acquired value a (t _n + j) in step S109.

According to this control, since the difference between the acquired value a (t _n + j) and the target acceleration w (t _n + j) in step S109 is small, when the arrival time T _c (t _n ) has elapsed, The speed v _a of the host vehicle 2 approaches the speed v _b of the preceding vehicle 3, and the inter-vehicle distance d between the host vehicle 2 and the preceding vehicle 3 is the safety distance _dr (t _{n +} ) calculated in step S106. ₁ ) will be approached. Further, since the acquired value a (t _n + j) is an acceleration that reduces the operation change amount Δu (t _n + j-1), the accelerator is not used until the arrival time T _c (t _n ) elapses. The amount of brake operation is almost constant.

And after step S110 is performed, it returns to step S102 and steps S102-S110 are performed again. This process, there is the time t _n subsequent time t _n +1 (for example, time t _n from the time T (FIG. 4 time reference) has elapsed) is performed when made to the current time, the time t _n + 1, data measured by the own vehicle measurement sensor 10 or the preceding vehicle measurement sensor 11 is used.

Vehicle of Specifically, in step S102, the speed v _a (t _n +1) of the vehicle 2, a preceding vehicle 3 at time _{t n +1, v b (t} n +1), the time t _n +1 The vehicle 2 and the preceding vehicle at time t _n +1 from the inter-vehicle distance d (t _n +1) and the speeds v _a (t _n +1) and v _b (t _n +1) between the vehicle 2 and the preceding vehicle 3 3 relative velocity v _ab (t _n +1) is obtained. In step S103, the arrival time until the vehicle 2 reaches the position of the preceding vehicle 3 at time _{t n +1 T c (t n} +1) is calculated, in step S105, the arrival time T _c (t _n By dividing (+1) at a predetermined time interval T, a plurality of prediction intervals N (t _n +1) are set. In step S107, the target acceleration w (t _n + 1 + j) of the own vehicle 2 is calculated for each prediction section N using the speed v _a (t _n +1) of the own vehicle 2 at time t _n +1. Calculated every (t _n +1). Further, in step S108, the time t _n +1 and the predicted acceleration y _p of the vehicle 2 in j time later _{(t n + 1 + j)} , the j-2 hours later at the current time t _n +1, the time t operation variation occurs until j-1 hour ahead of _{n +1 Δu (t n + j} -1) and the evaluation function as an input value J (t _n +1) is generated, in step S109, evaluation Based on the generalized predictive control for obtaining the input value that minimizes the output value of the function J (t _n +1), the acceleration a (t _n + 1 + j of the host vehicle 2 in each prediction section N (t _n +1) ) Is acquired. In step S110, the acceleration of the host vehicle 2 after time t _n +1 is controlled to the acquired value a (t _n + 1 + j) in step S109.

  And the process of step S102-S110 is repeated until the power supply of the traveling control system 1 is turned off by a user operating the switch in a vehicle interior.

  Next, details of steps S104 and S109 will be described.

Since the dynamic model created in step S101 (see Equation 1) includes the square value v _a ² of the speed v _a of the host vehicle 2, it is _a nonlinear equation with respect to v _a , and the evaluation function J (t _In order to obtain an analytical solution by generalized predictive control using _n ), linearization is required.

Therefore, in step S104, based on the dynamical model generated in step S101, the relationship between the force u acting on the speed v _a and the vehicle 2 of the vehicle 2 is a linear model is created that is linearly expressed . In step S109, the linear model created in step S104 is used, and the input value (predicted acceleration y _p (t _n + j) or operation change amount that minimizes the output value of the evaluation function J (t _n ) is used. An acting force u corresponding to Δu (t _n + j-1)) is obtained.

Specifically, in step S104, as shown in FIG. 6, first, a dynamic model at low speed in which the rolling resistance μ _r W (see Equation 1) dominates and the air resistance μ _l Av _a ² (Equation 1 And a dynamic model at high speed (see step S201). This process is executed based on the dynamic model of Equation 1.

Equation 15 shows a dynamic model at low speed running. At low speed, there is _a relationship of v _a ≦ √μ _r W / μ _l A (see equation 1), so equation 15 is a model in which the term of air resistance μ _l Av _a ² is deleted from equation 1. It has become.

Expression 16 shows a dynamic model at high speed running. At the time of high speed, there is _a relationship of v _a > √μ _r W / μ _l A (see Equation 1), so that the model of the rolling resistance μ _r W is deleted from Equation 1.

  Next, the dynamic model created in step S201 is transformed into a continuous time differential equation (step S202).

First, with respect to the dynamic model at the time of low speed traveling, the differential equation of Equation 17 is derived by modifying Equation 15.

Also, the dynamic model at high speeds, a v _a of the formula 16 at a 1 / z, by modifying Equation 16, the differential equation of Formula 18 is derived.

Next, Expression 17 which is a differential equation at low speed traveling and Expression 18 which is a differential equation at high speed traveling are converted into a discrete time model (step S203). In step S203, the time interval T used for setting each prediction interval N (t _n ) in step S203 of FIG. 3 is given as a discrete time.

Specifically, the equation 17 during low-speed running, the current time velocity v _a v _a1 Distant, the differential value of v _a v _a2 Distant, the differential value of the acting force u _r at the u _r2, Equation 19 To a discrete-time model of

Further, the equation 18 at high speeds, the inverse z of the current time velocity v _a z ₁ Distant, the differential value of z ₁ z ₂ Distant, the differential value of v _a v _a2 Distant, acting force u _{l Is} converted to a discrete-time model of Expression 20.

Next, a linear model used for generalized predictive control using the evaluation function J (t _n ) is derived from the discrete time model obtained in step S203 (step S204). This linear model is a model in which the relationship between the speed v _a of the host vehicle 2 and the force u acting on the host vehicle 2 is linearly expressed.

First, for low-speed running, the linear model shown in Equation 21 is derived from Equation 19.

In Equation 21, the differential value of the current time velocity v _a2 (t _n) is the differential value of the speed immediately before time _{t n -1 v a2 (t n} -1), the acting force immediately before time t _n -1 by adding the value obtained by multiplying the time interval T on the differential value u _r2 of u _r, is adapted to be calculated.

Further, for high speed traveling, the linear model shown in Expression 22 is derived from Expression 20.

In Equation 22, the differential value z ₂ (t _n ) of the reciprocal z of the current speed is the differential value z ₂ (t _n −1) of the reciprocal of the speed at the previous time t _n −1 and the previous time t _n −. by adding the value obtained by multiplying the time interval T on the differential value u _r2 of the first acting force u _r, it is calculated.

Then, in step S109 of FIG. 3, the acting force u (t _n ) corresponding to the input value that minimizes the output value of the evaluation function J (t _n ) is calculated using the linear models of equations 21 and 22.

Specifically, first, Formula 23 is derived by transforming Formula 21 when traveling at a low speed.

Moreover, Formula 24 is guide | induced by transforming Formula 22 about the time of high speed driving | running | working.

Then, by adding the acting force u _r (t _n ) calculated by the equation 23 and the acting force u _l (t _n ) calculated by the equation 24 by the equation 25, the above-described acting force u (t _n ) is calculated.

An acceleration a (t _n + j) that minimizes the output value of the evaluation function J (t _n ) can be obtained by inputting the acting force u (t _n ) calculated by Expression 25 into Expression 1. .

According to the present embodiment, the acceleration after the current time t _n is controlled by the acceleration a (t _n + j) of the host vehicle 2 acquired based on the generalized predictive control using the evaluation function J (t _n ). Thus, the speed v _a of the own vehicle 2 is brought close to the speed v _b of the preceding vehicle 3, and the inter-vehicle distance d between the own vehicle 2 and the preceding vehicle 3 is set to the speed v of the own vehicle 2 at the current time t _{n. a} sky run distance v _a (t _n) t _r and the braking distance and ^{_{v a (t n) 2 /}} 2μg and the total value greater safety than the distance d _r (t _{n + 1} is calculated on the basis of (t _n) ). Thereby, the safe driving | running | working control which can avoid the rear-end collision to the preceding vehicle 3 is realizable. Further, according to the acceleration control described above, the accelerator or brake operation change amount Δu (t _n + j−1) is reduced in each time zone after the current time t _n corresponding to each prediction section N (t _n ). Thus, the operation amount for the host vehicle 2 can be made substantially constant. As a result, it is possible to realize traveling control with good riding comfort without causing a rapid speed change in the host vehicle 2. In the present embodiment, the target acceleration w (t _n + j) is set to a constant value within each prediction interval N (t _n ) in order to realize travel control in which the operation amount for the host vehicle 2 is substantially constant. Therefore, the target acceleration w (t _n + j) is calculated for each prediction interval N (t _n ) using Equation 4.

In addition, when the weighting coefficient λ _j (see Equation 5) of the evaluation function J (t _n ) is set small, an acceleration a (t _n + j) that tends to approach the target acceleration is output. For this reason, the responsiveness to the target acceleration w (t _n + j) can be enhanced. When the weighting coefficient λ _j of the evaluation function J (t _n ) is set large, the acceleration a (t _n + j) that tends to decrease the operation change amount Δu (t _n + j−1) is output. As a result, the amount of operation of the accelerator and the brake becomes more constant, so that the ride comfort of the driver is further improved and energy loss such as engine output can be kept small.

In generalized predictive control using the evaluation function J (t _n ), acceleration prediction is multistage prediction performed in a plurality of prediction intervals N (t _n ) after the current time t _n, so long-term acceleration prediction is possible. It becomes possible. Thereby, control performance improves.

Further, as shown in Equation 3, the inter-vehicle distance d (t _n ) between the host vehicle 2 and the preceding vehicle 3 is calculated based on the speed v _a (t _n ) of the host vehicle 2 at the current time t _n. When the traveling control is performed so as to approach the safe distance d _r (t _n ), when the host vehicle 2 is traveling at a high speed, the inter-vehicle distance d between the preceding vehicle 3 and the host vehicle 2 increases. When the vehicle is traveling at a low speed, the inter-vehicle distance d from the preceding vehicle 3 is shortened. Thereby, the adjustment of the inter-vehicle distance d according to the speed v _a (t _n ) of the host vehicle 2 can be realized.

Also, an arrival time T _c (t _n ) until the host vehicle 2 reaches the position of the preceding vehicle 3 at the current time t _n is calculated, and this is divided by the time interval T, so that a predicted acceleration time A plurality of prediction intervals N (t _n ) are set. As a result, the prediction interval N (t _n ), which is the acceleration target time, is variably set according to the arrival time T _c (t _n ). The accuracy of control performance is improved. Further, as the speed increases, the safe distance d _r (t _n ) increases, so when the host vehicle 2 travels at a high speed, the arrival time T _c (t _n ) becomes longer and the predicted section N (t _n ) The number increases. As a result, since the traveling control system 1 predicts acceleration for a long time, smooth traveling control is performed. Further, as the speed decreases, the safe distance d _r (t _n ) becomes shorter. Therefore, when the host vehicle 2 travels at a low speed, the arrival time T _c (t _n ) becomes shorter, so that the predicted section N (t _n ), The amount of calculation required for control is reduced. As a result, variable control can be realized depending on the inter-vehicle distance d (t _n ) and speed.

Further, generalized predictive control using the evaluation function J (t _n ) is executed using a linear model in which the relationship between the speed v _a of the host vehicle 2 and the force u acting on the host vehicle 2 is linearly expressed. As a result, the calculation load is reduced. Thereby, rapid traveling control is realizable.

  The present invention is not limited to the above-described embodiment, and various modifications can be made.

  For example, the travel control system 1 is not limited to the above-described automobiles, but also travels on vehicles such as trains and monorails, and mobile objects such as robots, electric wheelchairs, warehouses, and automatic transfer devices in FMS (Flexible Manufacturing System). Can be mounted for.

  The means for performing various processes in the travel control system 1 of the present embodiment can be realized by either a dedicated hardware circuit or a programmed computer. Here, the program may be provided by a computer-readable information recording medium such as a flexible disk or a CD-ROM. In this case, the program recorded on the computer-readable information recording medium is usually transferred to and stored in the storage unit 20 such as a hard disk. The program may be provided as a single application software, or may be incorporated in the software of the device as one function of the device.

  Next, a simulation performed by the traveling control system 1 will be described.

In the simulation, the following first to third travel patterns were set, and the responsiveness of the host vehicle 2 to the speed change of the preceding vehicle 3 was confirmed for each of these patterns. Table 1 shows the parameters used in the simulation.

FIG. 7 shows the relationship between the vehicle speed v _a (t _n ) / preceding vehicle speed v _b (t _n ) and time in the simulation of the first driving pattern, and FIG. 8 shows the simulation of the first driving pattern. 3 shows the relationship between the inter-vehicle distance d (t _n ) / safety distance d _r (t _n ) and time.

The first travel pattern is a travel pattern that assumes that the preceding vehicle 3 decelerates slowly after traveling at high speed. In this travel pattern, as shown in FIG. 7, the preceding vehicle 3 travels at 90 km / h for 15 seconds, and in the subsequent 10 seconds (15 to 25 seconds), at an acceleration of 0.8 m / s ² , 60 km / h. The vehicle is set to travel at a speed of 60 km / h. In the 15 seconds when the preceding vehicle 3 travels at 90 km / h, the host vehicle 2 also travels at 90 km / h. In the simulation of the first travel pattern, the responsiveness of the host vehicle 2 after 15 seconds was confirmed.

As shown in FIG. 7, in response to the preceding vehicle 3 starting to decelerate after 15 seconds, the host vehicle 2 has also started decelerating, and when the preceding vehicle 3 decelerates to 60 km / h, The speed v _a (t _n ) of the own vehicle 2 was also 60 km / h, which was consistent with the speed v _b (t _n ) of the preceding vehicle 3.

  Further, in 25 seconds (15 to 40 seconds) in which the host vehicle 2 and the preceding vehicle 3 decelerate, the speed change of the host vehicle 2 is decelerated with respect to the driver as compared to a constant speed change of the preceding vehicle 3. It was smooth without giving a sense of incongruity.

In addition, as shown in FIG. 8, in 25 seconds (15 to 40 seconds) in which the host vehicle 2 and the preceding vehicle 3 are decelerated, and in the subsequent 10 seconds, the host vehicle 2 controls the acceleration, thereby controlling the preceding vehicle. The vehicle traveled while maintaining the distance d (t _n ) between the vehicle and the vehicle 3 at the safety distance d _r (t _n ).

FIG. 9 shows the relationship between the host vehicle speed v _a (t _n ) / preceding vehicle speed v _b (t _n ) and time in the second driving pattern simulation, and FIG. 10 shows the second driving pattern simulation. 3 shows the relationship between the inter-vehicle distance d (t _n ) / safety distance d _r (t _n ) and time.

The second traveling pattern is a traveling pattern that assumes that the preceding vehicle 3 stops while the host vehicle 2 is traveling. In this traveling pattern, as shown in FIG. 9, the preceding vehicle 3 travels at 90 km / h for 15 seconds (0 to 15 seconds), and then reaches 2.08 m / s ² for 12 seconds (15 to 27 seconds). It is set to stop by deceleration. Further, in 15 seconds (0 to 15 seconds) in which the preceding vehicle 3 travels at 90 km / h, the host vehicle 2 also travels at 90 km / h. In the simulation of the second running pattern, the responsiveness of the host vehicle 2 after 15 seconds was confirmed.

  As shown in FIG. 9, the host vehicle 2 also started decelerating in response to the preceding vehicle 3 starting to decelerate after 15 seconds. In the 12 seconds (15 to 27 seconds) in which the preceding vehicle 3 decelerates, the host vehicle 2 gradually increases the braking force as the relative speed increases, and is responsive to the speed change of the preceding vehicle 3. I was decelerating fast.

Further, as shown in FIG. 10, in the 12 seconds (15 to 27 seconds) in which the preceding vehicle 3 decelerates, the host vehicle 2 maintains the safety distance d _r (t _n ) and avoids a rear-end collision. After the preceding vehicle 3 stops (after 27 seconds), the inter-vehicle distance d (t _n ) between the host vehicle 2 and the preceding vehicle 3 becomes 2 m (see Table 1) of the inter-vehicle distance d _min when stopped. It was maintained.

FIG. 11 shows the relationship between the own vehicle speed v _a (t _n ) / preceding vehicle speed v _b (t _n ) and time in the third driving pattern simulation, and FIG. 12 shows the third driving pattern simulation. 3 shows the relationship between the inter-vehicle distance d (t _n ) / safety distance d _r (t _n ) and time.

  The third travel pattern is a travel pattern in which another vehicle enters between the host vehicle 2 and the preceding vehicle 3. In this traveling pattern, the host vehicle 2 and the preceding vehicle 3 are initially set to travel at 100 km / h, and when 15 seconds have elapsed, another vehicle moves 60 m ahead of the host vehicle 2 at a speed of 90 km. It is set to interrupt at / h, and then the other vehicle accelerates to a speed of 100 km / h. And in the simulation of the 3rd run pattern, the responsiveness of the own vehicle 2 after other vehicles interrupted (15 seconds-) was checked.

In FIG. 11, 15 seconds elapsed before the dashed lines indicate the preceding vehicle 3 speed v _b (t _n), after 15 seconds the broken line shows the speed of other vehicles v _b (t _n) . In FIG. 12, the solid line before 15 seconds indicates the inter-vehicle distance d (t _n ) between the host vehicle 2 and the preceding vehicle 3, and the solid line after 15 seconds indicates the own vehicle 2 and other vehicles. The inter-vehicle distance d (t _n ) is shown.

As shown in FIG. 11, after another vehicle interrupts between the own vehicle 2 and the preceding vehicle 3 (after 15 seconds), the own vehicle 2 applied a strong braking force and decelerated. This is because the own vehicle 2 measures the speed v _b (t _n ) of the other vehicle according to the change of the vehicle traveling immediately before to the other vehicle, and calculates the safety calculated based on the measured value. This is because the inter-vehicle distance d (t _n ) between other vehicles is made closer to the distance d _r (t _n ) (see 15 to 18 seconds in FIG. 12).

Then, as shown in FIG. 12, after the inter-vehicle distance d (t _n ) matches the safety distance d _r (t _n ) (after 18 seconds), the host vehicle 2 sets the safety distance d _r (t _n ). I was following up to maintain.

Further, after the inter-vehicle distance d (t _n ) coincides with the safe distance d _r (t _n ) (after 18 seconds), as shown in FIG. 11, the speed change of the own vehicle 2 is the speed of other vehicles. Compared to the change, the driver was smooth and did not give a sense of incongruity due to deceleration.

In addition, as shown in FIG. 11, during the period from when the interruption of another vehicle occurs until the inter-vehicle distance d (t _n ) matches the safety distance d _r (t _n ) (15 to 18 seconds) The host vehicle 2 has caused a rapid speed change to bring the inter-vehicle distance d (t _n ) closer to the safe distance d _r (t _n ). However, according to the present invention, by increasing the weighting coefficient λ _j in Expression 5 or decreasing the weighting coefficient γ in Expression 4, the speed change caused by the interruption as described above is suppressed to improve riding comfort. can do.

  The present invention can be applied to travel control of an automatic conveyance device in an automobile, a train, a monorail, a robot, an electric wheelchair, a warehouse, and an FMS.

DESCRIPTION OF SYMBOLS 1 Travel control system 2 Own vehicle 3 Leading vehicle 10 Own vehicle measurement sensor 11 Leading vehicle measurement sensor 12 Control device 20 Memory | storage part 21 Control part 22 Interface 30 Throttle actuator 31 Brake actuator

Claims (7)

A traveling control system mounted on a moving body that is operated for traveling,
By dividing the distance between the moving object at the current time and the preceding object traveling in front of the moving object by the speed of the moving object at the current time, the position of the preceding object at the current time is determined by the moving object. An arrival time calculating means for calculating an arrival time until reaching
By dividing the arrival time at a predetermined time interval, a prediction interval setting unit that sets a plurality of prediction intervals serving as acceleration prediction target times; and
At the time when the arrival time has elapsed, the speed of the moving body is brought close to the speed of the preceding object, and the distance between the moving body and the preceding object is calculated based on the speed of the moving body at the current time. Target acceleration calculating means for calculating a target acceleration of the moving body that can be approximated to a safe distance larger than the total of the free running distance and the braking distance, for each prediction section;
By inputting the predicted acceleration of the mobile body in each prediction section and the operation change amount to the mobile body between two consecutive prediction sections, the target acceleration and the predicted acceleration in each prediction section An evaluation function generating means for generating an evaluation function for adding and outputting the cumulative value relating to the difference between the two and the cumulative value relating to each operation change amount;
Based on generalized predictive control for obtaining an input value that minimizes the output value of the evaluation function, the acceleration of the mobile object in each prediction interval is acquired, and the acceleration of the mobile object after the current time is obtained as the acquired value. A travel control system comprising acceleration control means for controlling.   The target acceleration in each prediction section is a value obtained by multiplying a value obtained by dividing the difference between the distance between the moving object and the preceding object at the current time and the safety distance by the arrival time and a predetermined weighting factor. 2. The travel control according to claim 1, wherein the travel control is calculated by adding a relative speed between the moving object and the preceding object at a current time and dividing the added value by the arrival time. system. The cumulative value related to the difference between the target acceleration and the predicted acceleration in each predicted section is a value obtained by summing the square values of the differences between the target acceleration and the predicted acceleration in each predicted section.
The cumulative value related to each operation change amount is a value obtained by summing a value obtained by multiplying a square value of the operation change amount of the input value in two consecutive prediction intervals by a predetermined weighting coefficient. Item 3. The travel control system according to item 1 or 2. A dynamic model creating means for creating a dynamic model indicating the relationship between the force acting on the moving body and the acceleration of the moving body;
The travel control system according to any one of claims 1 to 3, wherein the acceleration control means acquires the acceleration of the moving body in each prediction section using the dynamic model. Based on the dynamic model created by the dynamic model creating means, linear model creating means for creating a linear model in which the relationship between the speed of the moving body and the force acting on the moving body is linearly expressed is further provided. And
The acceleration control means calculates, using the linear model, a force acting on the moving body corresponding to an input value that minimizes an output value of the evaluation function, and calculates a force acting on the moving body. The travel control system according to claim 4, wherein an acceleration of the moving body in each prediction section is acquired by inputting to a model. A control program for controlling a travel control system mounted on a moving body where a travel operation is performed,
By dividing the distance between the moving object at the current time and the preceding object traveling in front of the moving object by the speed of the moving object at the current time, the position of the preceding object at the current time is determined by the moving object. An arrival time calculation procedure for calculating the arrival time until reaching,
By dividing the arrival time at predetermined time intervals, a prediction interval setting procedure for setting a plurality of prediction intervals serving as acceleration prediction target times;
At the time when the arrival time has elapsed, the speed of the moving body is brought close to the speed of the preceding object, and the distance between the moving body and the preceding object is calculated based on the speed of the moving body at the current time. A target acceleration calculation procedure for calculating a target acceleration of the moving body that can be approximated to a safe distance larger than the total of the free running distance and the braking distance, for each prediction section;
By inputting the predicted acceleration of the mobile body in each prediction section and the operation change amount to the mobile body between two consecutive prediction sections, the target acceleration and the predicted acceleration in each prediction section An evaluation function generation procedure for generating an evaluation function that adds and outputs the cumulative value related to the difference between the cumulative value and the cumulative value related to each operation change amount;
Based on generalized predictive control for obtaining an input value that minimizes the output value of the evaluation function, the acceleration of the mobile object in each prediction interval is acquired, and the acceleration of the mobile object after the current time is obtained as the acquired value. A control program for causing the travel control system to execute an acceleration control procedure to be controlled.   A computer-readable recording medium on which the control program according to claim 6 is recorded.