Systems and methods for providing speed profiles for autonomous vehicles

Abstract

This invention relates to a system and method for providing speed profiles for autonomous vehicles. A system for providing speed profiles for autonomous vehicles includes: a vehicle driving information prediction device and a speed profile generation device; wherein the vehicle driving information prediction device includes: a navigation unit configured to set information about a driving route and a target driving time; a 3D map information providing unit configured to search for slope information of the driving route set by the navigation unit; and a vehicle driving information providing unit; wherein the speed profile generation device includes: a vehicle energy consumption calculation unit configured to calculate the energy consumption of the vehicle at its current speed when the vehicle is traveling along the set driving route; and a speed profile calculation unit configured to execute a dynamic programming algorithm to calculate a target speed profile based on distance.

Description

Technical Field

[0001] This invention relates to a system and method for providing speed profiles for autonomous vehicles. Background Technology

[0002] The autonomous vehicles to be released in the future are those that can identify the condition of the vehicle and its surroundings and drive themselves from the point of origin to the predetermined destination without driver intervention.

[0003] When examining the current level of an autonomous vehicle, it is reaching a semi-autonomous driving level, which involves the application of various types of Advanced Driver Assistance Systems (ADAS). These ADAS include: cruise control technology that controls the vehicle to travel at a predetermined speed or in a driver-defined normal mode; Advanced Smart Cruise Control (ASCC) that automatically adjusts the distance to the vehicle ahead while traveling at a preset speed; Lane Departure Warning System (LDWS) and Lane Keeping Assist System (LKAS) that maintain lane keeping and prevent lane departure.

[0004] The above description is only for the purpose of helping to understand the background of the present invention and is not intended to imply that the present invention falls within the scope of related technologies already known to those skilled in the art. Summary of the Invention

[0005] This invention relates to a system and method for providing speed profiles for autonomous vehicles. Specific embodiments relate to a system and method configured to enable the autonomous vehicle to drive based on an optimal speed profile calculated from driving information and the environment, thereby improving fuel economy.

[0006] One goal is to enable autonomous vehicles to generate stable driving paths by taking into account real-time changes in the traffic environment and avoiding collisions with surrounding dynamic obstacles. Another goal for autonomous vehicles is to optimize vehicle fuel efficiency based on speed curves while driving the generated driving path.

[0007] Therefore, embodiments of the present invention provide a system and method for providing a speed curve for an autonomous vehicle. The system and method provide a target speed curve to optimize fuel economy when the autonomous vehicle travels a preset route (preset distance) over a predetermined duration, and provide the target speed curve as the target speed of the autonomous vehicle traveling the preset route, thereby improving the fuel efficiency of the autonomous vehicle.

[0008] In one embodiment of the present invention, a system for providing a speed curve for an autonomous vehicle is provided. The system includes a vehicle driving information prediction device and a speed curve generation device. The vehicle driving information prediction device includes: a navigation unit configured to set information about a driving route and a target driving time, and to provide the set information to the speed curve generation device; a 3D map information providing unit configured to search for slope information of the driving route set by the navigation unit, and to provide the searched slope information to the speed curve generation device; and a vehicle driving information providing unit configured to provide the vehicle's current speed information and driving distance information to the speed curve generation device. The speed curve generation device includes: a vehicle energy consumption calculation unit configured to calculate the energy consumption of the vehicle at its current speed when the autonomous vehicle is driving along the set driving route; and a speed curve calculation unit configured to calculate a distance-based target speed curve by performing a dynamic programming algorithm based on the information provided by the vehicle driving information prediction device and the vehicle energy consumption calculation unit.

[0009] In another embodiment of the present invention, a method for providing a speed curve for an autonomous vehicle is provided. The method includes: setting a driving route for the autonomous vehicle using a navigation unit; searching for slope information appearing in the driving route using a 3D map information providing unit; providing the vehicle's current speed information and driving distance information to a speed curve generation device using a vehicle driving information providing unit; calculating the energy consumption of the vehicle at its current speed using a vehicle energy consumption calculation unit when the autonomous vehicle is driving along the driving route; and calculating a target speed curve on the driving route by executing a dynamic programming algorithm based on the driving route, slope information, speed information, driving distance information, and energy consumption using a speed curve calculation unit.

[0010] As described above, the system according to one embodiment and the method according to another embodiment provide the following effects.

[0011] First, as autonomous vehicles travel along a route from origin to destination, a reference speed curve can be provided to optimize fuel economy, thereby improving fuel efficiency.

[0012] Second, compared to driving on a constant speed curve based on existing automatic cruise control, it can guide driving on an optimal speed curve calculated based on information about the desired driving route and the environment, thereby improving fuel economy.

[0013] Third, even for non-autonomous vehicles, it can provide optimal speed curves suitable for the desired driving route and environment as driving guidance information.

[0014] Fourth, when the autonomous vehicle is an electric or hybrid vehicle, it can be guided to drive using the optimal speed curve calculated based on the desired driving route information and the environment, thereby reducing the consumption of battery state of charge (SOC).

[0015] Fifth, when the autonomous vehicle is an electric or hybrid vehicle, it can be guided to drive using the optimal speed curve calculated based on information about the desired driving route and the environment, thus providing the advantage of more efficient power distribution between the engine and the electric motor. Attached Figure Description

[0016] The above and other objectives, features and advantages of the embodiments of the present invention will become clearer from the following detailed description when taken in conjunction with the accompanying drawings, wherein:

[0017] Figure 1 This is a block diagram illustrating a system for providing speed curves for an autonomous vehicle according to an embodiment of the present invention;

[0018] Figure 2 This is a flowchart illustrating a method for providing a speed curve for an autonomous vehicle according to an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram comparing a speed curve provided by a system for providing speed curves for autonomous vehicles according to an embodiment of the present invention with a speed curve provided by a conventional automatic cruise control;

[0020] Figure 4 This is a schematic diagram illustrating the speed curve calculation process of an autonomous vehicle according to an embodiment of the present invention, wherein the calculation process is performed in each segment divided according to the distance of the driving route;

[0021] Figure 5A This is a schematic diagram comparing the speed of an autonomous vehicle traveling on a predetermined route for a predetermined duration using a speed curve provided by a system for providing speed curves for autonomous vehicles according to an embodiment of the present invention, with the speed of an existing vehicle traveling on the same route for a predetermined duration using a speed curve provided by an existing automatic cruise control.

[0022] Figure 5B It is to divide each vehicle into Figure 5A The diagram illustrates a comparison of the state of charge (SOC) consumption of a vehicle after traveling at the indicated speed, wherein the autonomous vehicle travels using a speed curve provided by a system for providing speed curves for autonomous vehicles according to an embodiment of the present invention, while the conventional vehicle travels using a speed curve provided by conventional automatic cruise control.

[0023] Figure 6 This is a schematic diagram illustrating traffic information, etc., that can be utilized in the process of providing speed profiles for autonomous vehicles according to an embodiment of the present invention;

[0024] Figure 7 This is a schematic diagram illustrating an example of calculating a target speed curve by utilizing energy consumption and the weighted sum of travel time for each road segment. Detailed Implementation

[0025] In the following description, exemplary embodiments of the invention will be illustrated with reference to the accompanying drawings. Throughout the drawings, the same reference numerals will denote the same or similar parts.

[0026] Figure 1 This is a block diagram illustrating a system for providing speed curves for an autonomous vehicle according to an embodiment of the present invention, wherein reference numeral 100 indicates a vehicle driving information prediction device and reference numeral 200 indicates a speed curve generation device.

[0027] The vehicle driving information prediction device 100 is a device installed in the vehicle that provides various types of information about the required driving route to the speed curve generation device 200 before driving, and includes a navigation unit 110, a 3D map information providing unit 120, an intelligent transportation system (ITS) information providing unit 130, and a vehicle driving information providing unit 140 related to autonomous driving.

[0028] The navigation unit 110 searches for the route from the starting point to the destination that the driver has already entered, thereby setting the vehicle's driving route and simultaneously setting the target driving time. Furthermore, the navigation unit 110 sends information about the set driving route and target driving time to the speed curve generation device 200, and simultaneously sends it to the 3D map information providing unit 120 and the ITS information providing unit 130.

[0029] The 3D map information providing unit 120 searches for distance-based slope information in the driving route sent from the navigation unit 110, and provides the searched slope information to the speed curve generating device 200.

[0030] The ITS information providing unit 130 searches for traffic signal information, vehicle congestion information (average vehicle speed), speed limit information, etc., that exist in the driving route sent from the navigation unit 110, and provides them to the speed curve generation device 200.

[0031] The vehicle driving information providing unit 140 provides the speed curve generating device 200 with information such as the distance to the vehicle ahead, the distance traveled on the driving route, and the current speed as the driving information of the current vehicle.

[0032] On the other hand, the speed curve generation device 200 is a processor installed in the vehicle that provides a speed curve for obtaining optimal fuel economy on a set driving route based on various information provided by the vehicle driving information prediction device 100 as described above, and includes a vehicle energy consumption calculation unit 210, a speed curve calculation unit 220, a speed curve recalculation unit 230, etc.

[0033] When the vehicle travels along the set driving route, the vehicle energy consumption calculation unit 210 calculates the energy consumption at the current speed and provides the calculated energy consumption to the speed curve calculation unit 220.

[0034] For example, the vehicle energy consumption calculation unit 210 calculates energy consumption, such as the state of charge (SOC) of an electric vehicle, the equivalent fuel consumption of a hybrid vehicle, and the fuel consumption of an internal combustion engine, and provides the calculated energy consumption to the speed curve calculation unit 220.

[0035] When the vehicle travels along the set driving route, the speed curve calculation unit 220 uses various types of information provided by the vehicle driving information prediction device 100 as described above to perform a dynamic programming algorithm, thereby calculating a target speed curve based on distance.

[0036] In this scenario, the target speed curve can be provided as a reference speed curve for optimizing fuel efficiency to the controller used for driving control of autonomous vehicles. As a result, autonomous vehicles travel on the set driving route at speeds that meet the reference speed curve, thereby promoting improved fuel economy.

[0037] Furthermore, even in non-autonomous vehicles, a target speed curve can be provided as guidance for improving fuel efficiency on desired driving routes.

[0038] The speed curve recalculation unit 230 compares the vehicle speed calculated based on the target speed curve as described above with the current speed of the vehicle provided by the vehicle driving information providing unit 140, and recalculates the target speed curve if there is a significant difference between them.

[0039] Here, the speed curve calculation process of the embodiment of the present invention based on the above configuration will be described sequentially.

[0040] Figure 2 This is a flowchart illustrating a method for providing a speed curve for an autonomous vehicle according to an embodiment of the present invention.

[0041] First, in S101, it is determined whether to use the navigation unit 110 installed in the vehicle to set the driving route of the autonomous vehicle.

[0042] For example, the driver uses the navigation unit 110 to set the desired driving route from the starting point to the destination.

[0043] Next, in step S102, the vehicle's driving route set in step S101 is provided to the speed curve generation device 200.

[0044] In addition, the driving route and target driving time information set by the navigation unit 110 are sent to the speed curve generation device 200, the 3D map information providing unit 120, and the ITS information providing unit 130.

[0045] Subsequently, in S103, the 3D map information providing unit 120 searches for distance-based slope information in the driving route sent from the navigation unit 110, and provides the slope information about the driving route set in step S101 to the speed curve generating device 200.

[0046] In addition, in S104, the ITS information providing unit 130 searches for traffic signal information, vehicle congestion information (average vehicle speed), speed limit information, etc., that exist in the driving route sent from the navigation unit 110, and then provides the searched information to the speed curve generation device 200.

[0047] In addition, in S105, the vehicle driving information providing unit 140 provides the speed curve generating device 200 with the distance to the vehicle in front, the driving distance on the driving route, and the current speed information as the driving information of the current vehicle.

[0048] Subsequently, in S106, when the vehicle is traveling along the set driving route, the vehicle energy consumption calculation unit 210 calculates the energy consumption at the current speed and provides the calculated energy consumption to the speed curve calculation unit 220.

[0049] For example, in the case of an electric vehicle, the vehicle energy consumption calculation unit 210 calculates the current battery SOC consumption and provides the calculated current battery SOC consumption to the speed curve calculation unit 220.

[0050] Next, in S107, the speed curve calculation unit 220 executes a dynamic programming algorithm, in which various types of information provided by the vehicle driving information prediction device 100 are replaced as described above, thereby calculating a target speed curve, which is an optimal speed curve for improving fuel efficiency on a set driving route.

[0051] More specifically, in the dynamic programming algorithm, the speed curve calculation unit 220 substitutes gradient information, traffic signal information, vehicle congestion information for each road segment, speed limit information, driving distance, energy consumption, etc., into the set driving route to calculate the target speed curve, which is the optimal speed curve used to improve fuel efficiency on the set driving route.

[0052] For example, the dynamic programming algorithm executed by the velocity curve calculation unit 220 is performed by the following equations 1 to 4.

[0053] As shown in Equation 1 below, the dynamic programming algorithm defines the vehicle speed v(d) based on distance d as the state variable, and the control variable u(d) based on distance d as the control variable (d = 1, 2, 3, ..., D). Next, the goal of the dynamic programming algorithm is to find the optimal speed curve v(d) function based on distance, such that when the vehicle travels from its first drive (d = 1) to its destination (d = D), the v(d) function satisfies the necessary cost function J. 1，D Minimum optimal cost function J * 1，D .

[0054] [Equation 1]

[0055]

[0056]

[0057] v(0)=v initial

[0058] v(D)=v final

[0059] In Equation 1, the initial velocity v(0) and final velocity v(d) of the vehicle are defined as V... initial and v final Vehicle acceleration It can be represented by the vehicle powertrain model function as follows: The control variable u(d) can be expressed as the torque of the power source (or motor torque for electric vehicles).

[0060] The instantaneous cost function L for distance d is determined based on v(d) and u(d) and can be expressed as the sum of battery energy consumption ΔSOC and the travel time Δtime for each w-weighted segment, as shown in Equation 2 below. Furthermore, estimates of the change in SOC can be used... To calculate the ΔSOC and Δtime required for the vehicle to travel the distance from d-1 to d.

[0061] [Equation 2]

[0062] L(v(d), u(d))=ΔSOC+ω·Δtime

[0063]

[0064]

[0065] On the other hand, J k，D It can be expressed as Equation 3 below, which represents the cost function of the route from distance d = k to distance d = D.

[0066] [Equation 3]

[0067]

[0068] Furthermore, according to the dynamic programming algorithm, the optimal cost function J from distance d = k to distance d = D is... * k，D It can be expressed as Equation 4 below.

[0069] [Equation 4]

[0070] J * k，D (v(k))=min{L(v(k), u(k))+J * k+1，D (v(k+1))}

[0071] Based on equations 1 to 4 above, the speed curve calculation unit 220 can easily calculate the target speed curve, which is the optimal speed curve v(d) for improving fuel economy on the set driving route.

[0072] Furthermore, in the process of using dynamic programming to search for vehicle speed v(d) based on distance d, traffic signal information of vehicles, traffic congestion information of each road segment, and speed limit information are used as constraints on the state variable (vehicle speed). Dynamic programming can only find vehicle speed curves that satisfy these constraints.

[0073] Here, the dynamic programming algorithm can calculate each cost function as the speed changes from v(d) to the next speed v(d+1), thereby searching for the optimal route. During the search for the next speed v(d+1), speed constraints can be applied to the search range of the next speed v(d+1), ensuring that speeds that do not meet the constraints are excluded when calculating the optimal speed curve (e.g., when searching for the next speed v(d+1) from the current speed v(d), speeds higher than the maximum speed should not be included in the search range of the next speed v(d+1)).

[0074] Reference Figure 6The maximum or minimum speed of a vehicle can be simply applied to a dynamic programming algorithm, and the optimal speed curve for a vehicle can be generated by specifying a speed range (e.g., average speed +5 km / h and average speed -5 km / h) using traffic congestion information or the average speed of vehicles on each road segment. In the case of traffic signal information, the predicted travel time is estimated based on the vehicle's speed curve information, thereby limiting the speed at the corresponding location when the traffic light is red. As a result, the traffic signal information can be reflected in the vehicle's speed curve.

[0075] At this time, the speed curve calculation unit 220 can divide the set driving route into multiple segments with arbitrary variations, and can calculate the target speed curve with the lowest fuel consumption within a predetermined time by using the sum of the energy consumption of each segment based on the current speed of each segment and the weighted driving time.

[0076] In this scenario, when a driving route is divided into multiple segments, each segment is not uniformly divided but can be variably divided to provide the optimal segment based on the established driving route.

[0077] An implementation scheme for calculating the target speed curve using the sum of energy consumption and weighted travel time for each road segment is as follows.

[0078] Reference Figure 7 When calculating the optimal speed curve from point A to point C, the speed from point A to point B can be defined as B-1, B-2, B-3, and B-4. Then, excluding B-4 which does not meet the speed limit, the instantaneous cost function L is calculated for each of B-1, B-2, and B-3.

[0079] Furthermore, assuming the speed changes linearly from A to B-1, the required vehicle torque can be calculated from the speed difference using the vehicle powertrain model, and the SOC consumption can be estimated based on the calculated torque.

[0080] Assuming Figure 7 As shown, the instantaneous cost function (L=ΔSOC+ω.Δtime) calculated at point B-1 is 0.4791, so the cost function of point B-1 is defined as 0.4791. In the same way, the cost functions of points B-2 and B-3 are defined as 0.1519 and 0.1656, respectively.

[0081] Similarly, when calculating the instantaneous cost function (L = ΔSOC + ω·Δtime) for each of the speeds B-1, B-2, and B-3 changing to C, for example, assuming the cost function for changing from B-1 to C is 0.2022, the cost function for changing from B-2 to C is 0.1605, and the cost function for changing from B-3 to C is 0.1321, then since the minimum sum of the cost functions is 0.2977(0.1656 + 0.1321), it can be seen that when moving from point A to point C, the optimal route is from point A through point B-3 to point C.

[0082] In this way, the speed is discretized according to the distance using a dynamic programming algorithm, and the instantaneous cost function (the sum of battery consumption and weighted required travel time) for each speed route is calculated, thereby obtaining the optimal speed curve as a solution.

[0083] Furthermore, in order to reduce the computational load of dynamic programming algorithms and effectively optimize the target velocity curve, such as Figure 4 As shown, the driving route can be divided into multiple segments that can be arbitrarily changed, and after setting the receding horizon of each segment, the target speed curve can be calculated using each segment.

[0084] More specifically, the target speed curve is calculated for each segment, but this calculation is performed in advance before the vehicle reaches the prediction horizon.

[0085] In this scenario, the driving route is defined as a segment by a predetermined distance (e.g., 4km) or a distance determined based on gradient information and the vehicle controller's calculated speed. The calculation of the target speed curve within the corresponding segment using a dynamic programming algorithm must be completed before the vehicle reaches the corresponding segment.

[0086] Because dynamic programming algorithms require a large amount of computation to calculate the entire area the vehicle travels over, the entire area is divided into, for example... Figure 4 The algorithm is applied to multiple road segments, where the entire length of the segment is set as the rolling time domain. The dynamic programming algorithm is then executed within the defined road segments, and the final vehicle speed v is calculated. final Let's assume it's the average speed of vehicles on the corresponding road segment.

[0087] Furthermore, instead of utilizing the entire rolling time domain results in the dynamic programming algorithm's computation, only the speed curve results of the first part of a predetermined road segment (e.g., 75% of the segment) are used as the prediction time domain. Thus, the next segment begins at the end of the prediction time domain, not the end of the rolling time domain of the previous segment. This is done to prevent local optimization of the speed curve that can occur when the dynamic programming algorithm is computed by assuming the vehicle's final speed to be the average speed of the corresponding road segment.

[0088] Return to reference Figure 2 Next, the target speed curve calculated in step S107 is provided to the drive controller 300 (e.g., a motor controller for electric vehicles, an engine controller for hybrid vehicles, a hybrid power controller that is a higher-level controller of the motor controller, and an engine controller for internal combustion engine vehicles), so that in S108 the autonomous vehicle can travel at a speed according to the target speed curve in the set driving route.

[0089] For example, the drive controller 300 receives a target speed curve and controls the autonomous vehicle to travel at a speed according to the target speed curve on the driving route.

[0090] Reference Figure 3 The diagram is in Figure 3 In this invention, the target speed curve calculated as described above is compared with the speed curve obtained by existing automatic cruise control, which displays a constant speed, while the target speed curve represents a speed curve suitable for information and environment related to the driving route. As a result, driving at the target speed curve of this invention provides the advantage of improved fuel economy compared to driving at a constant speed curve according to existing automatic cruise control.

[0091] Figure 5A This is a schematic diagram of simulation results comparing the speed of an autonomous vehicle traveling on a predetermined route for a predetermined duration using a speed curve provided by a system for providing speed curves for autonomous vehicles according to an embodiment of the present invention, with the speed of an existing vehicle traveling on the same route for a predetermined duration using a speed curve provided by an existing automatic cruise control.

[0092] like Figure 5A As shown, the speed curve (solid line) of the existing automatic cruise control shows a constant speed, but the target speed curve (dashed line) of the embodiment of the present invention shows a speed curve that varies greatly depending on the information of the driving route and the environment.

[0093] Figure 5B It compares each vehicle by Figure 5AThe diagram illustrates the SOC consumption of a vehicle after traveling at a certain speed, wherein an autonomous vehicle travels using a speed curve provided by a system for providing speed curves for autonomous vehicles according to an embodiment of the present invention, while a conventional vehicle travels using a speed curve provided by conventional automatic cruise control.

[0094] like Figure 5B As shown, the remaining battery SOC after driving using the speed curve according to conventional automatic cruise control is 88.48%, while the remaining battery SOC after driving using the target speed curve of the embodiment of the present invention is 88.65%. As a result, battery SOC consumption can be reduced by approximately 11%.

[0095] [Table 1]

[0096]

[0097] In this way, when driving on a set route, the autonomous vehicle starts driving at a speed according to the target speed curve via the drive controller, and since the target speed curve is a reference speed curve for optimizing fuel efficiency, it can achieve the effect of improving fuel efficiency.

[0098] Reference Figure 2 In S109, it is checked whether the vehicle's current speed differs from the target speed curve. If the vehicle's current speed differs from the target speed curve, in S110, the target speed curve can be recalculated.

[0099] More specifically, when an autonomous vehicle is traveling at a speed according to a target speed curve, the vehicle speed may change depending on driver intervention or the vehicle's driving state, or the driving conditions and environment may change when the driver alters destination information via a navigation unit or other means. In such cases, a step is performed to recalculate the target speed curve.

[0100] Therefore, the speed curve recalculation unit 230 compares the target speed curve calculated by the speed curve calculation unit 220 with the current speed of the vehicle provided by the vehicle driving information providing unit 140. If there is a significant difference between them, the speed curve calculation unit 220 calculates a new target speed curve in the same way as the target speed curve is calculated using a dynamic programming algorithm.

[0101] Of course, the newly calculated target speed curve in step S110 is provided to the vehicle's drive controller, so that the autonomous vehicle continues to travel at a speed according to the target speed curve, thereby improving fuel economy compared to driving according to existing automatic cruise control.

[0102] As described above, the system and method for providing speed curves according to embodiments of the present invention provide speed curves for optimizing the fuel economy of autonomous vehicles, but can also be applied to non-autonomous vehicles to calculate speed curves for optimizing fuel efficiency, and then the speed curves can be used as fuel-efficient driving guidance.

[0103] While preferred embodiments of the invention have been described for illustrative purposes, those skilled in the art will understand that various modifications, additions, and substitutions can be made without departing from the scope and spirit of the invention as disclosed in the appended claims.

Claims

1. A system for a vehicle, the system comprising: Vehicle driving information prediction device; and Velocity curve generation device; The vehicle driving information prediction device includes: The navigation unit is configured to set information about the driving route and target driving time, and to provide the set information to the speed curve generation device; A 3D map information providing unit, configured to search for slope information of the driving route set by the navigation unit, and provide the searched slope information to the speed curve generation device; and The vehicle driving information providing unit is configured to provide the vehicle's current speed information and driving distance information to the speed curve generating device; The velocity curve generation device includes: A vehicle energy consumption calculation unit is configured to calculate the energy consumption of the vehicle at its current speed when the vehicle is traveling along a set driving route; and The speed curve calculation unit is configured to calculate a distance-based target speed curve by performing a dynamic programming algorithm based on information provided by the vehicle driving information prediction device and the vehicle energy consumption calculation unit. The speed curve calculation unit divides the set driving route into multiple segments that can be arbitrarily changed, and calculates the target speed curve by using the sum of the energy consumption of each segment and the weighted driving time based on the current speed of each segment.

2. The system for a vehicle according to claim 1, wherein, The vehicle driving information prediction device further includes an intelligent transportation system information providing unit, which is configured to search for traffic signal information, average vehicle speed, and speed limit information of the driving route set by the navigation unit, and provide the traffic signal information, average vehicle speed, and speed limit information to the speed curve generation device.

3. The system for a vehicle according to claim 1, wherein, The speed curve generation device further includes a speed curve recalculation unit configured to compare a target speed curve with the vehicle's current speed.

4. The system for a vehicle according to claim 3, wherein, The speed curve recalculation unit is configured to recalculate the target speed curve when the difference between the target speed curve and the vehicle's current speed exceeds a threshold.

5. The system for a vehicle according to claim 1, further comprising a drive controller configured to receive a target speed curve and control the vehicle to travel at a speed according to the target speed curve on a travel route.

6. A method for providing a speed profile for an autonomous vehicle, the method comprising: Use the navigation unit to set the vehicle's driving route; Search for slope information in the driving route; Determine the vehicle's current speed and distance traveled; Calculate the energy consumption at the current speed as the vehicle travels along the driving route; The target speed curve on the driving route is calculated by executing a dynamic programming algorithm based on the driving route, slope information, current speed information, driving distance information, and energy consumption. The calculation of the target velocity curve includes: The speed curve calculation unit divides the set driving route into multiple segments that can be changed arbitrarily; The target speed curve is calculated by summing the energy consumption of each road segment based on the current speed of each segment and the weighted travel time.

7. The method of claim 6, further comprising: Search for traffic signal information, average vehicle speed, and speed limit information along the driving route; It provides traffic signal information, average vehicle speed, and speed limit information to generate speed profiles.

8. The method according to claim 6, wherein, The vehicle is an electric vehicle, and the method further includes calculating the state of charge consumption of the battery.

9. The method according to claim 8, wherein, The dynamic programming algorithm is further based on the calculated state of charge consumption of the battery.

10. The method of claim 6, further comprising: The gradient information, traffic signal information, vehicle congestion information for each road segment, speed limit information, driving distance and energy consumption in the set driving route are provided to the dynamic programming algorithm. A dynamic programming algorithm is used to calculate a target speed curve, wherein the target speed curve includes an optimal speed curve for improving fuel economy on a set driving route.

11. The method of claim 6, further comprising: The vehicle's speed on the driving route is adjusted to a speed based on the target speed curve.

12. The method according to claim 11, wherein, Adjusting the vehicle's speed includes providing the target speed curve to the vehicle's drive controller.

13. The method of claim 6, further comprising: Compare the target speed curve with the vehicle's current speed.

14. The method according to claim 13, wherein, When the vehicle’s current speed differs from the target speed curve, the method further includes recalculating the target speed curve.

15. The method according to claim 14, wherein, Recalculating the target velocity curve involves using dynamic programming algorithms.

16. A vehicle comprising a system for providing a speed profile, the system comprising: Vehicle driving information prediction device; and Velocity curve generation device; The vehicle driving information prediction device includes: The navigation unit is configured to set information about the driving route and target driving time, and to provide the set information to the speed curve generation device; A 3D map information providing unit, configured to search for slope information of the driving route set by the navigation unit, and provide the searched slope information to the speed curve generation device; and The vehicle driving information providing unit is configured to provide the vehicle's current speed information and driving distance information to the speed curve generating device; The velocity curve generation device includes: A vehicle energy consumption calculation unit is configured to calculate the energy consumption of the vehicle at its current speed when the vehicle is traveling along a set driving route; and The speed curve calculation unit is configured to calculate a distance-based target speed curve by performing a dynamic programming algorithm based on information provided by the vehicle driving information prediction device and the vehicle energy consumption calculation unit. The speed curve calculation unit divides the set driving route into multiple segments that can be arbitrarily changed, and calculates the target speed curve by using the sum of the energy consumption of each segment and the weighted driving time based on the current speed of each segment. The vehicle in question is either an autonomous or semi-autonomous vehicle.

17. The vehicle according to claim 16, wherein, The vehicle driving information prediction device further includes an intelligent transportation system information providing unit, which is configured to search for traffic signal information, average vehicle speed, and speed limit information of the driving route set by the navigation unit, and provide the traffic signal information, average vehicle speed, and speed limit information to the speed curve generation device.

18. The vehicle according to claim 16, wherein, The speed curve generation device further includes a speed curve recalculation unit, which is configured to recalculate the target speed curve when the difference between the target speed curve and the current speed of the vehicle exceeds a threshold.

19. The vehicle of claim 16, further comprising a drive controller configured to receive a target speed curve and control the vehicle to travel at a speed according to the target speed curve on the driving route.

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