KR101393683B1 - Driving speed prediction system and method of vehicle - Google Patents

Abstract

The present invention relates to a system and method for predicting a running speed of a vehicle, and more particularly to a system and method for predicting a running speed of a vehicle, An acquisition unit; A traveling section determining section for determining a traveling section in which the vehicle travels based on current position information of the vehicle and the destination information; A traffic information obtaining unit obtaining at least one traffic information corresponding to the traveling section; And a traveling speed predicting unit for predicting the traveling speed of the vehicle in the traveling section according to the predetermined period based on the acquired at least one traffic information.
With this configuration, the system and method for predicting the running speed of a vehicle according to the present invention can predict a running speed of a vehicle according to a traffic situation, a road condition, and an operation pattern after confirming a predicted running section when a driver of the vehicle inputs a final destination. Thereby, the fuel efficiency of the vehicle can be improved.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a driving speed prediction system,

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a system and a method for predicting a running speed of a vehicle, and more particularly, to a system and a method for predicting a running speed of a vehicle in which a running speed of a vehicle is predicted in advance, .

In recent years, environmental and resource problems have become very serious problems, and the development of environmentally friendly vehicles is rapidly spreading in the automobile industry. As a result of these developments, electric vehicles (EV), plug-in hybrid vehicles (PHEV), general hybrid vehicles (HEV) and hybrid vehicles are being studied and marketed for environmentally friendly automobiles.

The hybrid vehicle is a next-generation environmental automobile that significantly reduces the amount of harmful gas emissions compared to conventional vehicles. The hybrid vehicle is equipped with an internal combustion engine and a battery engine of an electric vehicle at the same time, It is possible to convert the gasoline engine and the electric engine automatically in accordance with the road and the surrounding environment while driving the engine by merely combining the advantages of the engine and the electric engine.

In addition, the plug-in hybrid vehicle refers to a vehicle capable of increasing the battery capacity of a general hybrid vehicle so that the hybrid vehicle can be charged by a domestic power source and can travel at a certain distance in an electric vehicle mode.

Particularly, because of the rapid development of the battery technology, it is possible to mount a large-capacity battery, which is advantageous in that it can be applied to a conventional hybrid vehicle or a new power transmission structure to lower the vehicle operation cost.

These eco-friendly vehicles require energy management for proper use of the engine and battery, which are power sources. Particularly, in the case of plug-in hybrid vehicles, the energy management strategy is becoming an important issue because the fuel efficiency can be improved by varying the control strategy depending on the battery capacity, the structure of the vehicle, the driving condition, and the mileage. In addition, when external environmental variables are applied to energy management strategies, technology is required to minimize the fuel consumption while satisfying the driver 's demand power in the actual driving environment with various driving situations.

In order to reduce the fuel consumption of the vehicle, it is necessary to prevent sudden stoppage or sudden start of the vehicle during driving. However, there are various variables such as the signal condition in the driving section, the road condition and the traffic volume in the driving section Accordingly, it is difficult to accurately predict the traveling speed of the vehicle.

In order to solve the problems of the prior art as described above, the present invention provides a driving speed predicting system for a vehicle that increases a fuel efficiency of a vehicle by predicting a driving speed according to a road condition and a traffic condition, And methods.

According to another aspect of the present invention, there is provided a system for predicting a running speed of a vehicle, the system including: inputting destination information to which a vehicle desires to arrive; receiving GPS (Global Positioning System) An information obtaining unit to obtain the information; A traveling section determining section for determining a traveling section in which the vehicle travels based on current position information of the vehicle and the destination information; A traffic information obtaining unit obtaining at least one traffic information corresponding to the traveling section; And a traveling speed predicting unit for predicting the traveling speed of the vehicle in the traveling section based on the acquired at least one traffic information according to a predetermined period.

More preferably, it calculates a running speed according to a running section on the basis of a dynamic programming technique, confirms a vehicle's stop state or running state according to a next signal of the running section, And a traveling speed predicting unit that includes acquiring the terminal region speed.

More preferably, it is displayed in the form of a look-up table including the weight for the acceleration or deceleration of the vehicle and the weight for the running time of the vehicle according to the average speed, the cruising speed and the traffic per unit time in the traveling section And a traveling speed predicting unit.

In particular, the information may include GPS information including at least one of a current position of the vehicle, a mileage, an acceleration, a deceleration, and a ground slope of the road.

In particular, it may include traffic information including at least one of the number of traffic lights existing in the travel section, the distance between the traffic lights, the signal period, the limited speed per section, and the average speed per section.

According to an aspect of the present invention, there is provided a method for predicting a traveling speed of a vehicle, the method comprising: receiving destination information for a vehicle to be received; inputting GPS (Global Positioning System) Obtaining; Determining a traveling section in which the vehicle travels based on current position information of the vehicle and the destination information; Obtaining at least one traffic information corresponding to the traveling section; And estimating a traveling speed of the vehicle in the traveling section based on the acquired at least one traffic information according to a predetermined period.

Calculating a traveling speed according to a traveling section on the basis of a dynamic programming technique; Confirming a vehicle's stop state or running state according to a next signal of the travel section; And obtaining an initial starting speed and an ending speed of the vehicle based on the driving speed of the vehicle.

More preferably, a process of forming a look-up table including a weight for the acceleration or deceleration of the vehicle and a weight for the running time of the vehicle according to the average speed in the traveling section, the cruising speed, and the traffic volume per unit time ; ≪ / RTI > estimating a running speed of the vehicle further comprising:

In particular, the information may include GPS information including at least one of a current position of the vehicle, a mileage, an acceleration, a deceleration, and a ground slope of the road.

In particular, it may include traffic information including at least one of the number of traffic lights existing in the travel section, the distance between the traffic lights, the signal period, the limited speed per section, and the average speed per section.

A system and method for predicting a running speed of a vehicle according to the present invention is a system and method for predicting running speed of a vehicle which receives a final destination through a vehicle navigation from a driver of the vehicle and confirms the running section, By predicting the traveling speed, the fuel efficiency of the vehicle can be improved.

In addition, the traveling speed system and method of the vehicle of the present invention can predict in advance whether the electric power used as the power source of the vehicle is charged by predicting the traveling speed when the user travels the hybrid vehicle, .

1 is a block diagram of a system for predicting a traveling speed of a vehicle according to an embodiment of the present invention.
2 is a flowchart of a method of predicting a running speed of a vehicle according to another embodiment of the present invention.
3 is a schematic diagram showing a plurality of travel information necessary for predicting the traveling speed.
4 is a diagram showing a blinking period of a traffic light.
5 is a diagram showing a blinking period of a traffic light.
FIG. 6 is a flowchart illustrating a process of converting acquired traffic information to be applied to dynamic programming.
FIG. 7 is a graph for predicting travel time by traffic conditions.
8 is a diagram illustrating grid generation for generating a velocity profile in one subdivision.
9 is a graph showing a predicted running speed of the vehicle according to the running time.
10 is a graph showing an optimal direction for the next state according to the cost for each state.
11 is a graph showing the actual traveling speed of the vehicle obtained from the GPS information.
12 is a graph showing the predicted running speed and the actual running speed of the vehicle according to the present invention.
13 is a graph showing a predicted traveling speed of the vehicle in each section.
14 is a graph showing the predicted running speed of the vehicle according to the running distance.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT Hereinafter, the present invention will be described in detail with reference to preferred embodiments and accompanying drawings, which will be easily understood by those skilled in the art. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.

Hereinafter, the traveling speed predicting system for a vehicle according to the present invention will be described in detail with reference to FIG.

1 is a block diagram of a system for predicting a traveling speed of a vehicle according to an embodiment of the present invention.

1, the driving speed predicting system 100 of the present invention includes an information obtaining unit 120, a driving section determining unit 140, a traffic information obtaining unit 160, and a traveling speed predicting unit 180, .

The information obtaining unit 120 receives destination information to be moved from the driver through navigation attached to the vehicle, receives GPS (Global Positioning System) information about the vehicle, and obtains current position information of the vehicle. At this time, the GPS information includes at least one of the driving distance of the vehicle, the acceleration, the deceleration, and the ground surface inclination of the driving road, as well as the current position of the vehicle.

The travel section determination unit 140 determines a travel section that the vehicle wishes to travel based on the current position information of the vehicle and the destination information.

The traffic information obtaining unit 160 obtains at least one traffic information corresponding to the traveling section. At this time, the traffic information includes at least one of the number of traffic lights existing in the travel section, the distance between the traffic lights, the signal period, the limited speed per section, and the average speed per section.

The traveling speed predicting unit 180 repeatedly predicts the traveling speed of the vehicle in the traveling section based on the acquired at least one traffic information according to a predetermined period. The running speed predicting unit 180 calculates a running speed according to a running section on the basis of a dynamic programming technique and confirms a vehicle's stopping state or running state according to the next signal of a signal lamp in the running section, And obtains an initial start speed and a termination speed of the vehicle. In addition, the traveling speed predicting unit 180 estimates the traveling speed of the vehicle based on the average speed in the traveling section, the cruising speed and the traffic volume per unit time, and includes a weight for the acceleration or deceleration of the vehicle and a weight for the traveling time of the vehicle. Look up table. Dynamic programming is used to analyze the collected data so as to reduce the execution time of the algorithm and to perform a corresponding action when an algorithm has characteristics of partial problem repetition and optimal basic structure .

Hereinafter, a driving speed predicting method of a vehicle according to another embodiment of the present invention will be described in detail with reference to FIG.

2 is a flowchart of a method of predicting a running speed of a vehicle according to another embodiment of the present invention.

As shown in FIG. 2, the traveling speed prediction method of a vehicle according to the present invention is a method for predicting a traveling speed of a vehicle, which receives destination information on which a vehicle is to be moved from a driver through navigation attached to the vehicle, receives GPS (Global Positioning System) The current position information is obtained (S210). At this time, the GPS information includes at least one of a current position of the vehicle, a travel distance, an acceleration, a deceleration, and a ground surface inclination of the road.

(S220), based on the present location information of the vehicle and the destination information, to determine a predicted travel section that the vehicle is expected to travel.

Next, at least one piece of traffic information on the traveling section that the vehicle wants to travel is obtained (S230). In this case, the traffic information includes not only the number of traffic lights existing on the road, the distance between the traffic lights, and the signal period through the intelligent transport system but also the speed limit per section indicating traffic volume of the road, And an average rate of stars.

In this manner, the acquired at least one traffic information is substituted into a dynamic programming technique represented by Equation (1) below, and the traveling speed of the vehicle traveling on the road in the traveling section is repeated (S240).

In this case, E _driving (k) is the running energy of the vehicle, T (k) is the running time, a is the acceleration of the vehicle according to the traffic, d is the deceleration of the vehicle according to the traffic, Is a weight assigned to acceleration, and v is a weight assigned to deceleration.

Particularly, the stop state or the running state of the vehicle is confirmed according to the generation of the next signal of the traffic light from the traffic information obtained for the traveling road in the traveling region.

In addition, an initial start speed and a termination speed of the vehicle in the traveling section are obtained.

In addition to this, the average speed of the vehicle traveling in the traveling section obtained from the traffic information, the weight given to the acceleration or deceleration of the vehicle generated according to the cruising speed when the flow of the vehicle is smooth and the traffic volume per unit time, Up table including a weight given to a running time of a desired vehicle.

In particular, information necessary for predicting the traveling speed will be described with reference to FIG.

3 is a schematic diagram showing a plurality of travel information necessary for predicting the traveling speed.

First, a destination information of a vehicle to which a vehicle is to be received is received, information on the current position of the vehicle is obtained by receiving GPS (Global Positioning System) information from the outside, and based on the current position information of the vehicle and the destination information And determines a traveling section in which the vehicle travels.

Accordingly, at least one traffic information occurring in the traveling section is obtained. For example, the driving section determined according to the input of the destination information of the driver is divided into a plurality of detailed sections, and the divided traffic information of each section is input. Δd ₁ is the distance of the detail section _1, V _ss, 1 is the driving speed according to the normal state of the vehicle in the detailed section _1, V _avg, 1 is the average speed of the vehicle in the detailed section _1, V _lim, 1 is The speed limit of sub-section 1, Q _{veh, 1} receives the vehicle traffic of sub-section 1, respectively.

In this manner, the information necessary for applying the received traffic information to dynamic programming is changed and extracted. That is, Δd ₁ is the distance of the detail section _1, V _ss, 1 is the driving speed according to the normal state of the vehicle in the detailed section _1, V _avg, 1 is the average speed of the vehicle in the detailed section _1, V _{lim, 1} is the velocity limit of sub-interval 1, Q _{veh, 1} is the traffic flow of sub-interval ₁ , V _{0 , 1} is the initial velocity of sub-interval 1, V _{f , 1} is the termination velocity of sub- _{pred , 1} is the expected time at the end of the sub-section 1, and? t _{wait , 1} is the stop time in the traffic signal of the previous sub-section.

At this time, the traffic information related to the traffic signal may be as shown in FIG.

4 is a diagram showing a blinking period of a traffic light.

는 교통신호의 초록불이 점등되는 지속시간을 나타내고, Δ

는 교통신호의 노란불이 점등되는 지속시간, Δ

는 교통신호의 빨간불이 점등되는 지속시간,Δ

노란불의 휴지시간, Δ

는 빨간불의 휴지시간을 나타내는 것으로, 교통 신호등의 점멸주기를 확인할 수 있다. As shown in Fig. 4,

Represents the duration of time when the green light of the traffic signal is turned on, and?

Is the duration of the yellow light of the traffic light, Δ

Is the duration of the red light of the traffic light,

Downtime of yellow fire, Δ

Indicates the rest time of the red light, and the flashing cycle of the traffic light can be confirmed.

In order to actually measure the traffic information, the total traveling section is 7.5 km, and a total of 13 traffic lights are installed in the traveling section, so that the blinking period of the traffic signal according to the traveling section as shown in FIG. 5 can be confirmed.

In order to apply the acquired traffic information to the dynamic programming technique, the conversion process will be described in detail.

FIG. 6 is a flowchart illustrating a process of converting acquired traffic information to be applied to dynamic programming.

As shown in FIG. 6, traffic information for a specific sub-section i among the sub-segments divided into a plurality of sub-segments is input from the previously obtained traffic information (S310).

At this time, it is checked whether the initial speed of the extracted traffic information is 0 (S320).

If the initial velocity is 0, the lighting signal of the traffic signal of the previous detailed section i-1 with respect to the expected time? _{T pred , i-1} at the time of arrival at the end point for the previous detailed section i-1 of the detailed section i (S330).

At this time, when the lighting signal of the traffic signal of the previous detailed section i-1 is green, the driving time? T _{drv , i} of the detailed section i is obtained by subtracting the driving start time s from the distance? D _i of the detailed section i, And a value obtained by dividing the running speed according to the steady state of the vehicle by twice the acceleration a in the sub-section i, and the value obtained by dividing the running speed V _{ss , i} according to the steady state of the vehicle. In addition, the braking time? T _{brk , i} of the detailed section i is calculated by dividing the running start time s by the running speed V _{ss , i} according to the steady state of the vehicle in the detailed section i (S331).

과 동일하다고 판단한다(S332). Or the turn-on signal of the traffic signal of the previous detailed section i-1 is red, the stop time? T _{wait , i} in the traffic signal of the detailed section i is the stop time?

(S332).

에 이전 세부구간 i-1에서의 빨간불이 점등되는 시간인 Δ

를 더하여 획득할 수 있다(S333). On the other hand, when the turn-on signal of the traffic signal of the previous detailed section i-1 is yellow, the stop time? T _{wait , i} in the traffic signal of the detailed section i is?

Lt; RTI ID = 0.0 > i-1 < / RTI >

(Step S333).

Subsequently, the stop time? T _{wait , i} in the traffic signal of the detailed section i, the running time? T _{drv , i} of the detailed section i, the braking time? _{Brk , i} of the detailed section i and the previous detailed section i- 1 of the previous detailed section i-1 with respect to the estimated time? _{T pred , i-} 1 at the end point of the traffic I-1 (S340).

At this time, when the lighting signal of the traffic signal of the detailed section i is green, the expected time? _{T pred , i,} when arriving at the end point of the detailed section i, is the distance? D _i of the detailed section i from the steady state the traveling speed V _ss, stop time at the divided by _i, and a traffic signal of double the divided value of the detail section i acceleration a running speed V _{ss, i} of the normal state of the vehicle in a, a detail section i along Δt _wait, by adding a _i and a time when the expected arrival at the end point of the previously detailed interval Δt _{pred 1-i, i-1,} can be calculated (S341).

However, if the lighting signal of the traffic signal of Detail section i in red or yellow, is expected on arrival at the end point of the detail section _i Δt _pred, i is obtained by subtracting the running start time s in the distance Δd _i of detail interval i A value obtained by dividing the running speed V _{ss , i} according to the steady state of the vehicle in the detailed section i and a value obtained by dividing the running speed according to the steady state of the vehicle by twice the acceleration a in the detailed section i are added, , Subtracts the value obtained by dividing the traveling speed V _{ss , i} according to the steady state of the vehicle by the distance between the transmitter and the receiver of the traffic information in the detailed section i and then calculates the stopping time Δt _wait in the traffic signal of the detailed section i _{, i} and the expected time? t _{pred , i-1} at the end of the previous detailed section i-1 (S342).

If the initial speed is not 0, the stop time? T _{wait , i} in the traffic signal of the detailed section i is set to 0, and the driving time? T _{drv , i} of the detailed section _i is set to 0 i is set to a value obtained by subtracting the running start time s from the distance? d _i of the detailed section _i and dividing the running speed V _{ss , i} according to the steady state of the vehicle in the detailed section i, and the braking time? _{brk ,} The start time s is set to a value obtained by dividing the starting speed V _{ss , i} according to the steady state of the vehicle in the detailed section i (S350).

Subsequently, the stop time? T _{wait , i} in the traffic signal of the detailed section i, the running time? T _{drv , i} of the detailed section i, the braking time? _{Brk , i} of the detailed section i and the previous detailed section i- 1, the lighting signal of the traffic signal of the previous detailed section i-1 with respect to the estimated time? _{T pred , i-1} when arriving at the end point with respect to i-1 is checked (S360).

At this time, when the lighting signal of the traffic signal of the detailed section i is green, the expected time? _{T pred , i,} when arriving at the end point of the detailed section i, is the distance? D _i of the detailed section i from the steady state the traveling speed V _ss, is calculated by adding the time Δt _{pred, i-1} is expected on arrival at the end point of the value and the previous detailed interval i-1, divided by _i (S361) in accordance with.

However, if the lighting signal of the traffic signal of Detail section i in red or yellow, is expected on arrival at the end point of the detail section _i Δt _pred, i is obtained by subtracting the running start time s in the distance Δd _i of detail interval i The driving speed V _{ss , i} according to the steady state of the vehicle is divided by the distance d _i of the detailed section i in the detailed section i from the value obtained by dividing the driving speed V _{ss , i} according to the steady state of the vehicle in the detailed section i And subtracts the estimated time Δt _{pred , i-1} from the expected time at the end of the previous detailed section i-1 (S362).

As a result, the time that is expected on arrival at the end point of a detail section i calculated through the above process S342 Δt _{pred, i,} and a process time that is expected on arrival at the end point of a detail section i calculated through S362 Δt _{pred, i} The lighting signal of the traffic signal of the detailed section i is checked (S370).

Accordingly, when the lighting signal of the traffic signal is green, the termination speed _{Vf, i} of the detailed section i is the driving speed _{Vss , i} according to the steady state of the vehicle in the detailed section i (S371).

However, if the on-signal of the traffic signal is red or yellow, of a detail section i terminal velocity V _{f, i} is a 0 (S372).

As a result, the initial velocity V _{0 , i + 1} of the next detailed interval i + 1 becomes the final velocity V _{f, i} of the detailed interval i (S380).

The traffic information converted or extracted so as to be applicable to the dynamic programming is stored through the above-described process (S390).

Based on the calculated at least one traffic information, the traveling speed of the vehicle in the traveling section is predicted according to a predetermined period.

FIG. 7 is a graph for predicting travel time by traffic conditions.

As shown in FIG. 7, Δt _{pred , i} is the time expected when arriving at the end point of sub-section i, Δt _{wait , i} is the stopping time in the previous traffic signal and Δt _{drv ,} And? T _{brk , i} is the vehicle deceleration time in the sub-section i. Accordingly, the details of the stopping time and the deceleration time of the vehicle can be obtained in detail according to traffic conditions.

와, 다음 과정으로 최적 방향을 나타내는

및 최적방향으로의 주행시간

이 출력된다.The traffic information thus generated is applied to the dynamic programming to generate the speed profile in succession in the subdivided detail sections for the entire travel section. That is, the distance Δd _i of the detailed section i, the traveling speed V _{ss, I} according to the steady state of the vehicle in the detailed section i, the average speed V _{avg , I} of the vehicle, the limiting speed V _lim of the detailed section i _{, i} , the vehicle speed Q _{veh , I} , the initial speed V _{0 , i} of the detailed section i, and the termination speed V _{f , i} of the detailed section i are applied to the dynamic programming, respectively, Optimized Cost

And the next step is to show the optimal direction

And the travel time in the optimum direction

Is output.

Hereinafter, a lattice generation process for generating a velocity profile in one detailed section will be described in detail with reference to FIG.

8 is a diagram illustrating grid generation for generating a velocity profile in one subdivision.

As shown in FIG. 8, when information of a specific sub-section i is inputted from among the entire travel sections, a grid of x and y axes is generated. At this time, the x-axis represents the distance and the y-axis represents the speed. The lattice of the x-axis is defined as a stage stage, and the lattice of the y-axis is defined as a state state, and the distance s of each stage on the x-axis is set to vary according to the distance d of the detailed section i.

가 200m 이하일 경우에 x축 상의 각 스테이지의 거리

, 200m를 초과하고 1000m 이하인 경우에는 x축 상의 각 스테이지의 거리

, 1000m초과하는 경우에는 x축 상의 각 스테이지의 거리

가 되도록 설정되며, 또한 y축 격자의 경우에는 0.2m/s 간격으로 설정된다.Therefore, the distance of the sub-

The distance of each stage on the x axis

, And when it is more than 200m but not more than 1000m, the distance of each stage on the x axis

, And if it exceeds 1000 m, the distance of each stage on the x axis

And in the case of the y-axis lattice, it is set at an interval of 0.2 m / s.

The dynamic programming technique computes the cost to go from a state state on a particular stage stage to an arbitrary state state on the next stage stage and iteratively repeats this operation from the distance S _N to S _{0 in} the reverse direction, . Thus, all grids store local costs.

Then, when the initial velocity v _initial at the distance S ₀ and the final velocity v _final at the distance S _N are determined, a path having the minimum cost to go from the initial velocity v _initial to the final velocity v _final is determined. The path determination with minimum cost is expressed by the following equation (2).

In other words, the path L (k) having the minimum cost is obtained by multiplying the driving energy E _drv (k) of the vehicle by w _t , which represents the weight assigned to the running time, by T (k) of the Acc ⁴ (k) and the multiplied value and, Dec ⁴ (k) and the multiplied value of w _b represents the reduced amount representing the weight assigned to the reduction represents the acceleration amount to w _a represents the weight both can be obtained by the sum of have. At this time, the weight w _t Can be obtained through a function calculation on the traveling speed V _{ss , i} according to the steady state of the vehicle and the distance d _i between the detailed section i in the detailed section i, as shown in the following equation (3).

Further, w _a representing the weight assigned to the acceleration And w _b representing the weight assigned to the deceleration can be obtained through a functional operation on the average traveling speed V _{avg , i} of the detailed section _i and the limiting speed V _{lim , i} .

As a result, when the path where the total cost J consumed for traveling the distance is minimum is a state variable represented by x (s) in the process s and a control variable represented by u (s), the following equation . ≪ / RTI >

Thus, the generated path J is the result of the velocity profile for the running information of sub-section i.

9 is a flowchart showing dynamic programming.

As shown in Fig. 9, first, driving information is inputted (S410).

Thereafter, a grid consisting of an x-axis (stage stage) and a y-axis (state) is generated (S420). At this time, the number of stages is N, the number of states is M, the stage distance s on the x-axis is set to N-1, the number of stages, and the number of states k and The number of states j currently displayed on the stage s is set to 0, respectively.

Accordingly, the running time T, the cost Cost, and the cumulative cost C between j and k are calculated using the following Equations 4 to 6 (S430).

는 하기의 수학식 6을 통해 연산할 수 있다. First, the running time when j of the current stage s moves to k of the next stage s + 1

Can be calculated by the following equation (6).

는 스테이지간 거리이고, 상기

는 다음 스테이지에서 k의 속도이고, 상기

는 현재 스테이지 s의 j에서 속도를 나타낸다. At this time,

Is a distance between stages,

Is the velocity of k at the next stage,

Represents the velocity at j of the current stage s.

는 하기의 수학식 7을 통해 연산할 수 있다. Further, the cost required when j of the current stage s moves to k of the next stage s + 1

Can be calculated by the following equation (7).

는 현재 스테이지 s의 j가 다음 스테이지 s+1의 k로 이동할 때 주행에너지

와, 주행시간에 할당된 가중치를 나타내는 w_t에 현재스테이지 s에서 j가 다음 스테이지 s+1에서 k로 이동할 때 주행시간을 나타내는 Δ

를 곱한 값과, 가속에 할당된 가중치를 나타내는 w_a를 현재스테이지 s에서 j가 다음 스테이지 s+1에서 k로 이동할 때 가속량을 나타내는

의 4제곱과 곱한 값, 및 감속에 할당된 가중치를 나타내는 w_b를 현재 스테이지 s에서 j가 다음 스테이지 s+1에서 k로 이동할 때 감속량을 나타내는

의 4제곱과 곱한 값을 합산하여 획득할 수 있다. That is, the cost of moving j in the current stage s to k in the next stage s + 1

When the j of the current stage s moves to k of the next stage s + 1,

And w _t , which represents the weight assigned to the running time, represents the running time when j moves from the next stage s + 1 to k in the current stage s

And w _a , which represents the weight assigned to acceleration, representing the amount of acceleration when j moves from the next stage s + 1 to k in the current stage s

And w _b , which represents the weight assigned to deceleration, is expressed as a deceleration amount when j moves from the next stage s + 1 to k in the current stage s

And then multiplying the product by the fourth power of the product

는 하기의 수학식 8과 같이, 현재 스테이지 s의 j가 다음 스테이지 s+1의 k로 이동할 때 주행 파워

와, 현재스테이지 s에서 j가 다음 스테이지 s+1에서 k로 이동할 때 주행시간을 나타내는 Δ

를 곱한 값을 나타낸다. At this time, when j of the current stage s moves to k of the next stage s + 1,

When the j of the current stage s is moved to k of the next stage s + 1, as shown in Equation (8) below,

And DELTA representing the travel time when j moves from the next stage s + 1 to k in the current stage s

.

는 하기의 수학식 9를 통해 연산할 수 있다. Further, in the present stage s, when j moves from the next stage s + 1 to k,

Can be calculated by the following equation (9).

는 하기의 수학식 10을 통해 연산할 수 있다.In addition, in the present stage s, when j moves from the next stage s + 1 to k,

Can be calculated by the following equation (10).

는 다음 스테이지에서 현재 스테이지를 뺀 거리로서, 하기의 수학식 11을 통해 연산할 수 있다.In addition,

Is a distance obtained by subtracting the current stage from the next stage and can be calculated by the following equation (11).

The cumulative cost can be calculated through the following equation (12) for summing the traveling time and the required cost calculated through the equations (6) to (7).

In operation S440, it is determined whether k is equal to the maximum number of states that can be displayed on the current stage s (S440).

, 인덱스값

및 주행시간 Δ

을 연산한다(S450). If j is equal to the maximum number of states that can be represented on the current stage, the cumulative cost (j) representing the state j in the current stage s based on Equations (7) to

, Index value

And travel time Δ

(S450).

는 현재 스테이지 s에서의 스테이트 j가 0 부터 최대 M까지 이동할 때의 각각의 소요비용의 최소값을 산출한다. First, as shown in Equation (13) below, cumulative cost

Calculates the minimum value of each required cost when the state j in the current stage s moves from 0 to the maximum M.

는 현재 스테이지 s에서 다음 스테이지로의 최적 방향을 나타내는 인덱스값을 말하며, 이는 최대 변수 m으로 표기된다. At this time,

Is the index value indicating the optimal direction from the current stage s to the next stage, which is denoted by the maximum variable m.

는 스테이지 s에서 j가 다음 스테이지 s+1의 최대 스테이트 수 m으로 이동할 때까지 주행시간과 동일하다고 판단한다. Therefore, as shown in the following equation (15), the running time?

Judges that j is the same as the running time until j moves to the maximum state number m of the next stage s + 1 in the stage s.

Then, the optimized cost, index value, and travel time are stored.

However, if k is not equal to the maximum number M of states that can be displayed on the current stage s in step S440, k is incremented by one (S441), and the step S430 is repeated.

In addition, it is checked whether j is equal to the maximum number M of states that can be displayed on the current stage s (S460). If it is not the same, k is set to 0, j is incremented by 1, and the process of S430 is repeated (S461).

On the other hand, if j is equal to the maximum number M of states that can be represented on the current stage s, it is checked again whether the S is equal to N-1, which is the number of stages (S470).

Thereafter, if S is equal to N-1, which is the number of stages, result data for all stages and states are stored (S480).

Alternatively, if S is not equal to N-1, which is the number of stages, j and k are set to 0, s is decremented by 1, and then step 430 is repeated (S471) .

The optimum direction for the next state according to the cost calculated for each state calculated through the above-described equation and traffic information can be confirmed through FIG.

10 is a graph showing an optimal direction for the next state according to the cost for each state.

As shown in FIG. 10, a solid line can be confirmed when the initial speed is set to 0, and a speed profile that the solid line predicts according to the traffic conditions for the detailed section i of the travel section can be obtained.

Hereinafter, an experimental example of the traveling speed predicting method of the vehicle according to the present invention will be described.

In order to analyze the traveling speed of the actual road, nine one way driving was performed on the main road of about 7.5 km, and the number of the traffic lights existing in the driving section was 13 in total. The actual speed profile of the vehicle obtained through the GPS information is shown in Fig.

11 is a graph showing the actual traveling speed of the vehicle obtained from the GPS information.

As shown in FIG. 11, when the distribution of the speed data obtained from the GPS information is examined, it can be seen that the driving pattern of the driver varies depending on the vehicle travel time, the period of the traffic lights, the road congestion, and the average speed.

Also, it can be seen that the driving time of the vehicle is about 625 sec to 800 sec, which is about 3 minutes difference. Thus, the cycle of the traffic lights existing in the driving section and the road congestion greatly affect the driving speed of the vehicle Able to know.

In addition, the number of stoppage by the stop signal of the traffic light changes from 3 to 7, and it can be understood that the traveling speed must be accelerated or decelerated in accordance with the signal period of the signal in the road.

12 is a graph showing the predicted running speed and the actual running speed of the vehicle according to the present invention.

It can be seen that the predicted running speed of the vehicle indicated by the solid line and the actual running speed indicated by the dotted line are measured similarly as shown in Fig. 12 (a), and as shown in Fig. 12 (b) It can be seen that the variation rate is also measured in a similar manner to the predicted speed and actual speed. In addition, after dividing the entire travel section into a plurality of sections, the traveling speed of the vehicle for each section can also be predicted.

13 is a graph showing a predicted traveling speed of the vehicle in each section.

As shown in FIG. 13, after dividing a total of 15 sections into a total running section, each running speed for each section can be predicted and represented as one running speed profile with respect to time.

14 is a graph showing the predicted running speed of the vehicle according to the running distance.

As shown in FIG. 14, it can be seen from the start of the vehicle up to 500 m that the running acceleration of the actual vehicle is lower than the acceleration during the normal flat running due to the steep incline on the road, An error of about 130 m is generated. In addition, it can be seen that the prediction of the maximum speed, the acceleration / deceleration, the mileage, and the number of stopping times is similar to the actual running pattern, except for the fluctuation portion of the traveling speed during cruising.

Also, as shown in Fig. 15, it can be seen that the actual stopping time of the vehicle is similar to the predicted time when the stop signal of the traffic light is generated, as well as the predicted traveling speed of the vehicle according to the traveling time.

Further, the system and method for predicting the traveling speed of such a vehicle may be stored in a computer-readable recording medium on which a program for executing the computer is recorded. At this time, the computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. Examples of the computer readable recording medium include ROM, RAM, CD-ROM, DVD 占 ROM, DVD-RAM, magnetic tape, floppy disk, hard disk, optical data storage, and the like. In addition, the computer-readable recording medium may be distributed to network-connected computer devices so that computer-readable codes can be stored and executed in a distributed manner.

The system and method for predicting running speed of a vehicle according to the present invention predicts a running speed of a vehicle according to a traffic situation, a road condition and an operation pattern after confirming a predicted running section when a driver of the vehicle inputs a final destination, There is an effect that the efficiency can be improved.

Further, the traveling speed system and method of the vehicle of the present invention has the effect of predicting the traveling speed to the destination when the user travels the hybrid electric vehicle, thereby confirming whether or not the electric power used as the power source of the vehicle is charged .

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, Do.

120: information acquisition unit 140: travel section determination unit
160: traffic information obtaining unit 180: traveling speed predicting unit

Claims (12)

An information obtaining unit for receiving destination information to which the vehicle desires to arrive and receiving current location information of the vehicle by receiving GPS (Global Positioning System) information;
A traveling section determining section for determining a traveling section in which the vehicle travels based on current position information of the vehicle and the destination information;
A traffic information obtaining unit obtaining at least one traffic information corresponding to the traveling section; And
A traveling speed predicting unit for predicting a traveling speed of the vehicle in the traveling section according to a predetermined period based on the acquired at least one traffic information;
, ≪ / RTI &
The running speed predicting unit
A running speed according to a running section is calculated based on a dynamic programming technique, a stopping state or a running state of the vehicle is checked according to a next signal of the running section, and an initial start speed and a termination section speed A system for estimating the running speed of a vehicle to be acquired.
delete The method according to claim 1,
The running speed predicting unit
Up table including a weight for the acceleration or deceleration of the vehicle and a weight for the running time of the vehicle according to the average speed, the cruising speed, and the traffic volume per unit time in the traveling section, is displayed in the form of a look- Of the traveling speed of the vehicle.
The method according to claim 1,
The GPS information
Wherein the information includes at least one of a current position of the vehicle, a travel distance, an acceleration, a deceleration, and a ground surface inclination of the road.
The method according to claim 1,
The traffic information
A signal period, a limit speed for each section, and an average speed for each section of the vehicle.
Receiving destination information on which the vehicle desires to arrive, receiving GPS (Global Positioning System) information, and obtaining current position information of the vehicle;
Determining a traveling section in which the vehicle travels based on current position information of the vehicle and the destination information;
Obtaining at least one traffic information corresponding to the traveling section; And
Estimating a traveling speed of the vehicle in the traveling section according to a predetermined period based on the acquired at least one traffic information;
, ≪ / RTI &
The step of predicting the running speed of the vehicle
A traveling speed according to a traveling section is calculated based on a dynamic programming technique,
Confirming a vehicle's stop state or running state according to the next signal in the travel section; And
Obtaining an initial starting speed and a terminating speed of the vehicle in the traveling section;
And estimating the running speed of the vehicle.
delete delete The method according to claim 6,
The step of predicting the running speed of the vehicle
A step of forming a look-up table including a weight for acceleration or deceleration of the vehicle and a weight for driving time of the vehicle according to an average speed, a cruising speed, and a traffic volume per unit time in the traveling section;
And estimating the running speed of the vehicle.
The method according to claim 6,
The GPS information
Wherein the information includes at least one of a current position of the vehicle, a travel distance, an acceleration, a deceleration, and a ground slope of the road.
The method according to claim 6,
The traffic information
A signal period, a limit speed for each section, and an average speed for each of the sections.
A computer-readable recording medium storing a program for causing a computer to execute the method according to any one of claims 6 to 11.

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