Electronic device and lane determination method

Abstract

Disclosed are an electronic device and a lane determination method. The method according to an embodiment may comprise the steps of: calculating a cost function of each of a plurality of lanes included in a road on which a vehicle is traveling; and determining, as a target lane, a lane having the minimum cost among the plurality of lanes on the basis of the cost function. The cost function may be a numerical representation of traveling factors that occur when the vehicle travels on a lane corresponding to the cost function.

Description

Electronic devices and lane determination methods

[0001] The following disclosure relates to an electronic device and a method for determining a lane.

[0002] Autonomous vehicles may need to perceive their surroundings, plan routes based on those conditions, and drive safely and efficiently. In particular, in complex driving situations such as lane changes, it can be important for the vehicle to appropriately select not only the current lane but also the target lane.

[0003] Existing autonomous driving systems have primarily used rule-based methods to make lane decisions. This method operates based on predefined rules and algorithms, and may require users (e.g., engineers) to directly design the system's operation.

[0004] The background technology described above is possessed or acquired by the inventor in the process of deriving the content of the disclosure of the present application, and cannot necessarily be considered as prior art disclosed to the general public prior to the filing of this application.

[0005] A method for determining a lane according to one embodiment may include the operation of calculating a cost function for each of a plurality of lanes included in a road in which a vehicle is traveling. The method may include the operation of determining a lane having the minimum cost among the plurality of lanes as a target lane based on the cost function. The cost function may be a numerical representation of driving factors that occur when the vehicle travels in the lane corresponding to the cost function.

[0006] The above cost function may include one or more of the first to fifth parameters. The first parameter may relate to the cost representing the efficiency of the driving path for reaching a destination. The second parameter may relate to the cost required to prevent a collision with a vehicle in front of the vehicle. The third parameter may relate to the cost required to prevent a collision with a vehicle behind the vehicle. The fourth parameter may relate to the cost required to avoid an obstacle on the driving path. The fifth parameter may relate to the cost required to prevent reckless lane changes.

[0007] The operation of calculating the cost function for each of the plurality of lanes may include the operation of calculating the first parameter based on the number of lane changes required to reach the destination and the distance to the destination.

[0008] The operation of calculating the cost function for each of the plurality of lanes may include the operation of calculating the second parameter based on the distance between the vehicle and the vehicle ahead and the speed of the vehicle.

[0009] The operation of calculating the cost function for each of the plurality of lanes may include the operation of calculating the third parameter based on the distance between the vehicle and the vehicle behind and the relative speed of the vehicle behind with respect to the vehicle.

[0010] The operation of calculating the cost function for each of the plurality of lanes may include the operation of calculating the fourth parameter based on the time the obstacle existed when the obstacle is located in the far right lane during a right turn of the vehicle. The obstacle may include a stationary vehicle.

[0011] The operation of calculating the cost function for each of the plurality of lanes may include the operation of calculating the fifth parameter by applying a different penalty to the lane to be changed depending on whether the lane to be changed by the vehicle matches the driving path.

[0012] The plurality of lanes may include a first lane and a second lane. The operation of determining the lane having the minimum cost among the plurality of lanes as the target lane may include comparing the result value of the first cost function of the first lane and the result value of the second cost function of the second lane, and determining the lane corresponding to the cost function having the smaller result value as the target lane.

[0013] An electronic device for determining a lane according to one embodiment may include a processor. The electronic device may include a memory for storing instructions. The instructions may be executed individually or collectively by the processor to cause the electronic device to calculate a cost function for each of a plurality of lanes included in a road on which a vehicle is traveling. The instructions may be executed individually or collectively by the processor to cause the electronic device to determine, based on the cost function, the lane having the minimum cost among the plurality of lanes as a target lane. The cost function may be a numerical representation of driving factors that occur when the vehicle travels in the lane corresponding to the cost function.

[0014] The above cost function may include one or more of the first to fifth parameters. The first parameter may relate to the cost representing the efficiency of the driving path for reaching a destination. The second parameter may relate to the cost required to prevent a collision with a vehicle in front of the vehicle. The third parameter may relate to the cost required to prevent a collision with a vehicle behind the vehicle. The fourth parameter may relate to the cost required to avoid an obstacle on the driving path. The fifth parameter may relate to the cost required to prevent reckless lane changes.

[0015] The above instructions may be executed individually or collectively by the processor to enable the electronic device to calculate the first parameter based on the number of lane changes required to reach the destination and the distance to the destination.

[0016] The above instructions may be executed individually or collectively by the processor to cause the electronic device to calculate the second parameter based on the distance between the vehicle and the vehicle ahead and the speed of the vehicle.

[0017] The above instructions may be executed individually or collectively by the processor to enable the electronic device to calculate the third parameter based on the distance between the vehicle and the vehicle behind it and the relative speed of the vehicle behind it with respect to the vehicle.

[0018] The above instructions may be executed individually or collectively by the processor to cause the electronic device to calculate the fourth parameter based on the time the obstacle was present when the obstacle is located in the far right lane during a right turn of the vehicle. The obstacle may include a stationary vehicle.

[0019] The above instructions may be executed individually or collectively by the processor to cause the electronic device to calculate the fifth parameter by applying a different penalty to the lane to be changed depending on whether the lane to be changed by the vehicle matches the driving path.

[0020] The plurality of lanes may include a first lane and a second lane. The instructions may be executed individually or collectively by the processor to cause the electronic device to compare the output of a first cost function of the first lane and the output of a second cost function of the second lane, and to determine the lane corresponding to the cost function having a smaller output as the target lane.

[0021] FIG. 1 is a drawing for explaining an autonomous driving method according to one embodiment.

[0022] FIG. 2 is a block diagram illustrating hardware included in an autonomous driving device according to one embodiment.

[0023] FIG. 3 is an example of a lane determination system according to one embodiment.

[0024] FIG. 4 is a diagram illustrating a method for calculating a lane-by-lane cost function of a road in which a vehicle is traveling, according to one embodiment.

[0025] FIG. 5 is a diagram illustrating a method for optimizing a cost function according to one embodiment.

[0026] FIGS. 6a to 6c are drawings for explaining a method for determining a lane in various scenarios according to one embodiment.

[0027] FIG. 7 is an example of a flowchart of a method for determining a lane according to one embodiment.

[0028] FIG. 8 is an example of an electronic device according to one embodiment.

[0029] Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be modified and implemented in various forms. Accordingly, actual implementations are not limited to the specific embodiments disclosed, and the scope of this specification includes modifications, equivalents, or substitutions included in the technical concept described by the embodiments.

[0030] Terms such as "first" or "second" may be used to describe various components, but these terms should be interpreted solely for the purpose of distinguishing one component from another. For example, the first component may be named the second component, and similarly, the second component may be named the first component.

[0031] When it is stated that a component is "connected" to another component, it should be understood that it may be directly connected to or coupled with that other component, or that there may be other components in between.

[0032] The singular expression includes the plural expression unless the context clearly indicates otherwise. In this specification, terms such as "comprising" or "having" are intended to specify the existence of the described features, numbers, steps, actions, components, parts, or combinations thereof, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0033] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this specification.

[0034] Hereinafter, embodiments will be described in detail with reference to the attached drawings. In the description with reference to the attached drawings, identical components are given the same reference numeral regardless of the drawing number, and redundant descriptions thereof will be omitted.

[0035]

[0036] FIG. 1 is a drawing for explaining an autonomous driving method according to one embodiment.

[0037] Referring to FIG. 1, an autonomous driving device (e.g., the autonomous driving device (40) of FIG. 2) can be mounted on a vehicle to implement an autonomous driving vehicle (10). The autonomous driving vehicle (10) may be a vehicle capable of driving on its own without driver operation.

[0038] The autonomous driving device (40) mounted on the autonomous driving vehicle (10) may include various sensors for collecting surrounding situation information (e.g., sensor unit (41) of FIG. 2).

[0039] The autonomous driving device (40) can detect the movement of a preceding vehicle (20) operating in front through an image sensor and / or event sensor mounted on the front of the autonomous driving vehicle (10). The autonomous driving device (40) may further include sensors to detect other vehicles (30) operating in the adjacent lane as well as pedestrians around the autonomous driving vehicle (10), in addition to the front of the autonomous driving vehicle (10).

[0040] At least one of the sensors for collecting situational information around the autonomous vehicle (10) may have a predetermined field of view (FoV) as shown in FIG. 1. When a sensor mounted on the front of the autonomous vehicle (10) has a field of view (FoV) as shown in FIG. 1, information detected at the center of the sensor may have relatively high importance. This may be because the information detected at the center of the sensor contains most of the information corresponding to the movement of the preceding vehicle (20).

[0041] The autonomous driving device (40) processes information collected by the sensors of the autonomous driving vehicle (10) in real time to control the movement of the autonomous driving vehicle (10), while at least some of the information collected by the sensors can be stored in a memory device (e.g., memory system (47) of FIG. 2).

[0042]

[0043] FIG. 2 is a block diagram illustrating hardware included in an autonomous driving device according to one embodiment.

[0044] Referring to FIG. 2, the autonomous driving device (40) may include a sensor unit (41), a processor (46), a memory system (47), and a vehicle body control module (48), etc.

[0045] The sensor unit (41) may include a plurality of sensors (42-45). The plurality of sensors (42-45) may include an image sensor, an event sensor, an illuminance sensor, a GPS device, an accelerometer, etc. Data collected by the sensors (42-45) may be transmitted to a processor (46).

[0046] The processor (46) can store data collected by the sensors (42-45) in the memory system (47). The processor (46) can determine the movement of the vehicle by controlling the vehicle body control module (48) based on the data collected by the sensors (42-45).

[0047] The memory system (47) may include two or more memory devices and a system controller for controlling the memory devices. Each of the memory devices may be provided as a single semiconductor chip. In addition to the system controller of the memory system (47), each of the memory devices included in the memory system (47) may include a memory controller. The memory controller may include an artificial intelligence (AI) computation circuit, such as a neural network. The memory controller may generate computation data by assigning a predetermined weight to data received from the sensors (42-45) or the processor (46), and may store the computation data in the memory chip.

[0048] The vehicle body control module (48) can control the movement of the vehicle by receiving commands from the processor (46).

[0049]

[0050] FIG. 3 is an example of a lane determination system according to one embodiment.

[0051] Referring to FIG. 3, a lane decision system (300) may include a vehicle (310), a lane decision device (330), and a server (350). However, FIG. 3 is an example for explaining the present invention and should not be interpreted as limiting the scope of the present invention. For example, the lane decision device (330) may perform a lane decision method independently without a server (350).

[0052] A vehicle (310) may mean a person and / or a means of transport for transporting a person. The vehicle (310) may be an autonomous vehicle (10) shown in FIG. 1 or may include an autonomous driving device (40) shown in FIG. 2. The vehicle (310) may include, for example, a means of transport such as an automobile, a train, a ship, a boat, an aircraft, a kickboard and / or a bicycle.

[0053] The lane determination device (330) may be mounted inside the vehicle (310) or implemented outside the vehicle (310) (e.g., on a server (350)).

[0054] The lane determination device (330) can determine the lane in which the vehicle (310) will travel. The vehicle (310) may be traveling on a road that includes multiple lanes. The lane determination device (330) can calculate a cost function for each of the multiple lanes included in the road in which the vehicle (310) is traveling.

[0055] The cost function may represent the driving factors that occur when the vehicle (310) drives in the lane corresponding to the cost function. The cost function may be defined such that the risk (and / or inefficiency) that may occur during driving due to the driving factors is quantified as a parameter. A higher output value of the cost function (e.g., cost) may indicate that driving in a specific lane (e.g., the lane corresponding to the cost function) incurs a higher cost. Cost may be determined based on various driving factors, and the cost function may be defined by multiple parameters to reflect these driving factors in lane determination.

[0056] The cost function includes (or defines) a plurality of parameters (e.g., first to fifth parameters), each of which may be determined based on driving factors affecting the driving of the vehicle (310). Driving factors may include, but are not limited to, other vehicles driving around the vehicle (310), a driving path to reach a destination, obstacles on the driving path, and / or the number of lane changes.

[0057] The first parameter may relate to a cost representing the efficiency of the driving route to reach the destination. The first parameter may be determined based on the driving route to reach the destination.

[0058] The second parameter may be related to the cost required to prevent collisions with other vehicles traveling around the vehicle (310) (e.g., a vehicle in front of the vehicle (310)). The second parameter may be determined based on the relationship between the vehicle (310) and the vehicle in front of the vehicle (310).

[0059] The third parameter may be related to the cost required to prevent collisions with other vehicles traveling around the vehicle (310) (e.g., a vehicle behind the vehicle (310)). The third parameter may be determined based on the relationship between the vehicle (310) and the vehicle behind the vehicle (310).

[0060] The fourth parameter may relate to the cost required to avoid an obstacle on the driving path. The obstacle may include, for example, a vehicle that is stopped (or stationary) in the lane in which the vehicle (310) is driving (or is scheduled to drive). When the vehicle (310) makes a right turn, an obstacle may be located in the far right lane. In this case, the vehicle (310) may need to drive in a lane other than the far right lane to avoid the obstacle. The fourth parameter may be determined based on the time the obstacle is present (e.g., the time the stationary vehicle is stationary) when the obstacle is located in the far right lane during the vehicle (310)'s right turn.

[0061] The fifth parameter may relate to the costs required to prevent indiscriminate lane changes by the vehicle (310). If no separate penalty is imposed when the vehicle (310) changes lanes, the vehicle (310) may change lanes indiscriminately. To prevent this, the fifth parameter may be defined to impose a penalty on the changed lane (or the lane to be changed) if the vehicle (310) has changed lanes (or intends to change lanes). However, since it may be inefficient to impose the same penalty whether the vehicle (310) deviates from the driving path to the destination or not, the fifth parameter may be calculated by imposing a different penalty on the lane to be changed depending on whether the lane to be changed by the vehicle (310) matches the driving path to the destination.

[0062] In this specification, first to fifth parameters are defined according to driving factors that may influence lane determination, but the parameters are not limited thereto and may exist in various forms corresponding to various driving factors.

[0063] The lane determination device (330) can determine, based on a cost function, the lane having the minimum cost among a plurality of lanes as the target lane (e.g., the lane on which the vehicle (310) will travel). For example, it is assumed that the plurality of lanes includes a first lane and a second lane. The lane determination device (330) can determine the lane having the smaller result value (e.g., cost) as the target lane by comparing the result value of the cost function of the first lane (e.g., the cost incurred when the vehicle (310) travels in the first lane) and the result value of the cost function of the second lane (e.g., the cost incurred when the vehicle (310) travels in the second lane).

[0064] The server (350) may be a server that controls and manages the vehicle (310) and / or the lane determination device (330). The server (350) may be a server that monitors the vehicle (330) in real time and manages the vehicle (330). The server (350) may perform remote control of the vehicle (330).

[0065] The vehicle (310), lane determination device (330), and server (350) can communicate using a network (not shown). For example, the network may include a Local Area Network (LAN), a Wide Area Network (WAN), a Value Added Network (VAN), a mobile radio communication network, a satellite communication network, and combinations thereof. The network is a comprehensive data communication network that enables the vehicle (310), lane determination device (330), and server (350) to communicate smoothly with each other, and may include wired internet, wireless internet, and mobile wireless communication networks. Additionally, the wireless communication network may include, for example, Wi-Fi, Bluetooth, Bluetooth Low Energy, Zigbee, Wi-Fi Direct (WFD), Ultra-Wideband (UWB), Infrared Data Association (IrDA), Near Field Communication (NFC), but is not limited thereto.

[0066] Below, the method for determining the lane will be explained in detail with reference to FIGS. 4 to 8.

[0067]

[0068] FIG. 4 is a diagram illustrating a method for calculating a lane-by-lane cost function of a road in which a vehicle is traveling, according to one embodiment.

[0069] Referring to FIG. 4, a lane determination device (e.g., lane determination device (330) of FIG. 3) can determine the lane (410, 420) in which a vehicle (430) (e.g., vehicle (310) of FIG. 3) will travel.

[0070] The lane determination device (330) can calculate a cost function for each lane (410, 420). As shown in FIG. 4, it is assumed that the vehicle (430) is driving in lane (420), that there is a vehicle (440) behind the vehicle (430), and that there are vehicles (450, 460) in front of the vehicle (430).

[0071] The lane determination device (330) can calculate the cost function of the lane (420). The lane determination device (330) can calculate the parameters of the cost function of the lane (420) (e.g., first to fifth parameters) based on driving factors that may affect the vehicle (430) when driving on the lane (420). Below, the method for calculating each parameter will be described.

[0072] The lane determination device (330) can calculate a first parameter based on the number of lane changes required to reach a destination and the distance to the destination. The first parameter relates to a cost representing the efficiency of the driving route to reach the destination, and the lane determination device (330) can set the first parameter such that the less lane changes the vehicle (430) makes to reach the destination, the greater the efficiency. For example, the lane determination device (330) can determine the number of lane changes required for the vehicle (430) to reach the destination from its current location and the distance to the destination from information regarding the driving route. The lane determination device (330) can calculate the first parameter through the following mathematical formulas 1 and 2 based on the number of lane changes required for the vehicle (430) to reach the destination from its current location and the distance to the destination.

[0073]

[0074]

[0075] In Equations 1 and 2, route_utility represents the efficiency of the driving route (e.g., the parameter is set so that efficiency decreases as the number of lane changes increases when traveling the same distance), cost_route represents the first parameter, np.clip represents the numpy clip function, d represents the distance to the destination, num represents the number of lane changes required to reach the destination, s_lc represents the parameter for optimizing the cost function based on the first parameter, and eps represents epsilon, a value used to serve a stabilization role (e.g., to prevent the denominator from becoming zero).

[0076] The lane determination device (330) can calculate a second parameter based on the distance between the vehicle (430) and the vehicle (450) ahead and the speed of the vehicle (430). The second parameter relates to the cost required to prevent a collision with the vehicle (450) ahead, and the lane determination device (330) can set the second parameter such that the higher the probability of a collision with the vehicle (450) when changing lanes (420) based on the distance between the vehicle (430) and the vehicle (450) ahead and the speed of the vehicle (430), the higher the cost (e.g., the less safe distance there is from the vehicle (450), the higher the cost). For example, the lane determination device (330) can calculate the second parameter through the following mathematical formulas 3 to 5 based on the distance between the vehicle (430) and the vehicle (450) ahead and the speed of the vehicle (430).

[0077]

[0078]

[0079]

[0080] In mathematical formulas 3 through 5, s_lead represents the distance between the vehicle (430) and the vehicle (450) ahead, v_ego represents the speed of the vehicle (430), t_s_front represents a parameter for optimizing the cost function by the second parameter, s_min_front represents the minimum value of the safety distance with the vehicle (450) ahead, s_max_front represents the maximum value of the safety distance with the vehicle (450) ahead, s_gain_utility represents the safety with the vehicle (450) (e.g., the less safety distance with the vehicle (450), the more cost is incurred), and cost_s_gain represents the second parameter.

[0081] The lane determination device (330) can calculate a third parameter based on the distance between the vehicle (430) and the vehicle (440) behind it and the relative speed of the vehicle (440) to the vehicle (430). The third parameter relates to the cost required to prevent a collision with the vehicle (440) behind it, and the lane determination device (330) can set the third parameter so that the higher the probability of a collision with the vehicle (440) when changing lanes (420) based on the distance between the vehicle (430) and the vehicle (440) behind it and the relative speed of the vehicle (440) to the vehicle (430), the higher the cost (e.g., the shorter the distance to the vehicle (440) or the greater the difference in relative speed, the higher the cost). For example, the lane determination device (330) can calculate a third parameter through the following mathematical formulas 6 and 7 based on the distance between the vehicle (430) and the vehicle (440) behind it and the relative speed of the vehicle (440) to the vehicle (430).

[0082]

[0083]

[0084] In mathematical formulas 6 and 7, s_lag represents the distance between vehicle (430) and the vehicle (440) behind (e.g., defined as a negative number), v_lag represents the speed of the vehicle (440) behind, v_ego represents the speed of vehicle (430), and cost_safety represents the third parameter.

[0085] The lane determination device (330) can calculate a fourth parameter based on the time the obstacle exists when the vehicle turns right and an obstacle (e.g., a stopped (or stationary) vehicle) is located in the far right lane. When the vehicle (310) turns right, an obstacle may be located in the far right lane. In this case, the vehicle (310) may need to drive in a lane other than the far right lane to avoid the obstacle. Thus, the fourth parameter can be set to avoid a stopped vehicle located on the right-turn path when the vehicle (430) turns right. That is, the fourth parameter can be calculated only when there is a stopped vehicle in the far right lane when the vehicle (430) turns right. For example, unlike as shown in FIG. 4, when the vehicle (430) turns right and there is a stopped vehicle in the far right lane, the lane determination device (330) can calculate the fourth parameter through the following mathematical formulas 8 and 9 based on the time the stopped vehicle exists.

[0086]

[0087]

[0088] In Equations 8 and 9, static_age represents the time of existence of an obstacle (e.g., a stationary vehicle) (e.g., a number indicating how long it has been stopped), t_ref represents a parameter for optimizing the cost function by the fourth parameter, and cost_blockage represents the fourth parameter.

[0089] The lane determination device (330) can calculate the fifth parameter by applying a different penalty to the lane to be changed depending on whether the lane to be changed by the vehicle (430) matches the driving path. The fifth parameter is calculated to prevent indiscriminate lane changes, and a penalty may be applied to the lane to be changed when changing lanes. However, as described in FIG. 3, it may be inefficient to apply the same penalty whether the vehicle (310) deviates from the driving path to reach the destination or not; therefore, the fifth parameter may be calculated so that a penalty is applied differently depending on whether the lane change deviates from the driving path or not. For example, when the vehicle (430) changes to lane (420), the lane determination device (330) may apply a penalty of '1' to the fifth parameter if the change to lane (420) deviates from the driving path. In another example, the lane determination device (330) may apply a penalty of '0.5' to the fifth parameter when the vehicle (430) changes to the lane (420) and the change to the lane (420) does not deviate from the driving path.

[0090] The lane determination device (330) can calculate the cost function of the lane (420) by summing the first to fifth parameters. The lane determination device (330) can calculate the cost of the lane (420) by summing the cost and / or penalty calculated according to the first to fifth parameters. For example, the lane determination device (330) can calculate the cost function of the lane (420) as shown in Equation 10 below.

[0091]

[0092] In Equation 10, f represents the cost function, cost_route represents the first parameter, cost_s_gain represents the second parameter, cost_safety represents the third parameter, cost_blockage represents the fourth parameter, and cost_lane_change represents the fifth parameter, and inside represents the weight of each parameter.

[0093] The method for calculating the cost function of the lane (410) is substantially the same as the method for calculating the cost function of the lane (420) described above, so the redundant explanation below will be omitted.

[0094] As described above, the lane determination device (330) can determine the lane with the minimum cost as the target lane by comparing the output values ​​of the cost function calculated for each lane (410, 420).

[0095] Below, with reference to FIG. 5, we will explain how to optimize the cost function calculated for each lane (410, 420) (e.g., how to optimize the parameters of the cost function).

[0096]

[0097] FIG. 5 is a diagram illustrating a method for optimizing a cost function according to one embodiment.

[0098] Referring to FIG. 5, operations 510 to 530 represent the process of optimizing the cost function.

[0099] In operation 510, a lane determination device (e.g., the lane determination device (330) of FIG. 3) can acquire driving data. The driving data may include ground truth values, which are actual driving data of the vehicle. The lane determination device (330) can optimize (or adjust) the parameters of the cost function by comparing the lane determination through the cost function to be calculated later with the ground truth values. This will be explained in operation 520.

[0100] In operation 520, the lane determination device (330) can calculate a cost function for each lane (e.g., lanes (410, 420) of FIG. 4) and optimize the parameters of each cost function. As the method for calculating the cost function has been described in detail with reference to FIG. 4, a redundant description will be omitted below.

[0101] The lane determination device (330) can perform GA (genetic algorithm)-based optimization by comparing the actual value and the inferred value (e.g., the target lane determined through the cost function (e.g., the lane with the minimum cost by comparing the output value (e.g., cost) of the cost function for each lane (410, 420)). For example, let us assume that in the actual value, the vehicle (430) is driving in lane (410). The lane determination device (330) determines the parameters of the cost function of lane (410) and lane (420) (e.g., the weights of the parameters (e.g., of Equation 10)) so that the cost of lane (410) is minimized. inside The lane determination device (330) can be adjusted. As another example, the lane determination device (330) can compare the inferred value with the actual value, and if the inferred value differs from the actual value, it can apply a penalty to the parameter of the lane-specific cost function. If the inferred value is lane (420) and the actual value is lane (410), the lane determination device (330) can apply a penalty to the cost function of lane (420) to make it larger than the cost function of lane (410).

[0102] The lane determination device (330) can perform calculation and optimization of multiple cost functions for each lane (410, 420) by repeating operation 520. That is, the lane determination device (330) can calculate multiple cost functions for one lane (410) and individually perform optimization of the calculated multiple cost functions.

[0103] In operation 530, the lane determination device (330) can obtain a plurality of optimized parameter sets for each lane (410, 420) by repeating operation 520 (e.g., first to fifth parameters as one set). The lane determination device (330) can obtain a final parameter set for each lane (410, 420) by determining one of the plurality of optimized parameter sets according to an experiment or a pre-set rule. The lane determination device (330) can obtain a cost function according to the final parameter set for each lane (410, 420).

[0104]

[0105] FIGS. 6a to 6c are drawings for explaining a method for determining a lane in various scenarios according to one embodiment.

[0106] Referring to FIG. 6a, when a vehicle (605) (e.g., vehicle (330) of FIG. 3 and / or vehicle (430) of FIG. 4) turns right at an intersection, there may be a stationary (or stopped) vehicle (610) immediately after the right turn. The lane determination device (330) can calculate a cost function of lane (615) such that the cost of lane (615) (e.g., the left lane of the far right lane) is minimized by a fourth parameter in order to avoid the vehicle (610) when the vehicle (610) is present during the right turn. When the cost function of lane (615) is minimized, the lane determination device (330) determines lane (615) as the target lane, thereby allowing the vehicle (605) to turn right while avoiding the vehicle (610).

[0107] Referring to FIG. 6b, a scenario in which a vehicle (620) (e.g., vehicle (330) of FIG. 3 and / or vehicle (430) of FIG. 4) must turn right at an intersection is described. To turn right at an intersection, the vehicle (620) may need to drive in lane (630) and turn right into lane (640). At this time, if there is a vehicle (625) stopped in front of the vehicle (620) on lane (630), the vehicle (620) must drive around the vehicle (625). The lane determination device (330) can calculate a cost function of lane (635) such that the cost of lane (635) (e.g., a lane next to lane (630)) is minimized by a fourth parameter. As a result, lane (635) is determined as the target lane, allowing the vehicle (620) to change from lane (630) to lane (635) and drive. When the vehicle (620) passes the vehicle (625), the lane determination device (330) can calculate the cost function of the lane (630) such that the cost of the lane (630) is minimized by the first parameter (e.g., cost regarding the driving path to the destination) because the vehicle (620) must turn right according to the driving path. As a result, the vehicle (620) can return to the lane (630), turn right, and drive into the lane (640).

[0108] Referring to FIG. 6c, let us describe a scenario in which a vehicle (645) (e.g., vehicle (330) of FIG. 3 and / or vehicle (430) of FIG. 4) must make a left turn at a forward intersection. When a vehicle (645) traveling in lane (655) must make a left turn, it may be necessary to consider the possibility of a collision with a vehicle (650) in the left lane. When the vehicle (645) maintains its travel in lane (655) and a suitable space is created between it and the vehicle (650) in area (660), the lane determination device (330) can calculate a cost function for the left lane such that the cost of the left lane of lane (645) is minimized by a second parameter (e.g., set to prevent a collision with a vehicle in front) and / or a third parameter (e.g., set to prevent a collision with a vehicle behind). As a result, the vehicle (645) can change lanes to the left from lane (645) and enter lane (665).

[0109]

[0110] FIG. 7 is an example of a flowchart of a method for determining a lane according to one embodiment.

[0111] Referring to FIG. 7, operations 710 and 730 may be performed sequentially, but are not limited thereto. For example, the two operations may be performed in parallel. Operations 710 and 730 may be substantially identical to the operation of the lane determination device (e.g., lane determination device (330) of FIG. 3) described with reference to FIG. 1 through 6. Accordingly, a detailed description is omitted.

[0112] In operation 710, the lane determination device (330) can calculate a cost function for each of a plurality of lanes included in the road in which the vehicle (e.g., vehicle (310) of FIG. 3) is driving. The cost function may represent the driving factors that occur when the vehicle (330) drives in the lane corresponding to the cost function. The cost function may include one or more of the first to fifth parameters.

[0113] The lane determination device (330) can calculate a first parameter based on the number of lane changes required to reach a destination and the distance to the destination. The lane determination device (330) can calculate a second parameter based on the distance between the vehicle (330) and a vehicle in front (e.g., vehicle (450) in FIG. 4) and the speed of the vehicle (330). The lane determination device (330) can calculate a third parameter based on the distance between the vehicle (330) and a vehicle behind (e.g., vehicle (440) in FIG. 4) and the relative speed of the vehicle behind (440) with respect to the vehicle (330). The lane determination device (330) can calculate a fourth parameter based on the time the obstacle (e.g., a stationary vehicle) is located in the far right lane when the vehicle (330) turns right. The lane determination device (330) can calculate the fifth parameter by applying a different penalty to the lane to be changed depending on whether the lane to be changed by the vehicle (330) matches the driving path.

[0114] In operation 730, the lane determination device (330) can determine the lane having the minimum cost among a plurality of lanes as the target lane based on a cost function. For example, the plurality of lanes may include a first lane and a second lane. The lane determination device (330) can determine the lane corresponding to the cost function having the smaller result value as the target lane by comparing the result value of the first cost function of the first lane and the result value of the second cost function of the second lane.

[0115]

[0116] FIG. 8 is an example of an electronic device according to one embodiment.

[0117] Referring to FIG. 8, the electronic device (800) may include a memory (810) and a processor (830). The description with reference to FIG. 1 through 7 may be applied in the same way to FIG. 8. For example, the difference determination device (330) of FIG. 3 may be the electronic device (800).

[0118] Memory (810) can store instructions (e.g., programs) executable by the processor (830). For example, the instructions may include instructions for executing the operation of the processor (830) and / or the operation of each component of the processor (830).

[0119] The memory (810) can be implemented as a volatile memory device or a non-volatile memory device.

[0120] Volatile memory devices can be implemented as DRAM (dynamic random access memory), SRAM (static random access memory), T-RAM (thyristor RAM), Z-RAM (zero capacitor RAM), or TTRAM (Twin Transistor RAM).

[0121] Non-volatile memory devices can be implemented as EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, MRAM (Magnetic RAM), Spin-Transfer Torque (STT)-MRAM, Conductive Bridging RAM (CBRAM), FeRAM (Ferroelectric RAM), PRAM (Phase change RAM), Resistive RAM (RRAM), Nanotube RRAM, Polymer RAM (PoRAM), Nano Floating Gate Memory (NFGM), holographic memory, Molecular Electronic Memory Device, or Insulator Resistance Change Memory.

[0122] The processor (830) can process data stored in memory (810). The processor (830) can execute computer-readable code (e.g., software) stored in memory (810) and instructions triggered by the processor (830).

[0123] The processor (830) may be a data processing device implemented in hardware having a circuit having a physical structure for executing desired operations. For example, the desired operations may include code or instructions included in a program.

[0124] For example, a data processing device implemented in hardware may include a microprocessor, a central processing unit, a processor core, a multi-core processor, a multiprocessor, an Application-Specific Integrated Circuit (ASIC), and a Field Programmable Gate Array (FPGA).

[0125] The processor (830) can cause the electronic device (800) to perform one or more operations by executing code and / or instructions stored in memory (810). The operations performed by the electronic device (800) may be substantially the same as the operations performed by the difference determination device (330) described with reference to FIGS. 1 through 7. Such redundant descriptions are omitted.

[0126]

[0127] The embodiments described above may be implemented as hardware components, software components, and / or combinations of hardware and software components. For example, the devices, methods, and components described in the embodiments may be implemented using a general-purpose computer or a special-purpose computer, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. In addition, other processing configurations, such as parallel processors, are also possible.

[0128] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or command the processing unit independently or collectively. Software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave in order to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on computer-readable recording media.

[0129] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may store program instructions, data files, data structures, etc., either individually or in combination, and the program instructions recorded on the medium may be those specifically designed and configured for the embodiment or those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

[0130] The hardware device described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0131] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can apply various technical modifications and variations based thereon. For example, suitable results may be achieved even if the described techniques are performed in a different order than described, and / or if the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0132] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

Claims

1. Regarding the method of determining the lane, The operation of calculating a cost function for each of the multiple lanes included in the road on which the vehicle is traveling; and Operation of determining the lane having the minimum cost among the plurality of lanes as the target lane based on the above cost function Includes, The above cost function is, A method that quantifies and represents driving factors occurring when the above vehicle travels on a lane corresponding to the above cost function.

2. In Paragraph 1, The above cost function is, One or more of the first to fifth parameters Includes, The above first parameter is, It concerns the cost representing the efficiency of the driving route to reach the destination, and The above second parameter is, This concerns the costs required to prevent a collision with a vehicle in front of the above-mentioned vehicle, and The above third parameter is, This concerns the costs required to prevent a collision with a vehicle behind the above-mentioned vehicle, and The above fourth parameter is, This relates to the cost required to avoid obstacles on the aforementioned driving path, and The above fifth parameter is, A method concerning the costs required to prevent indiscriminate lane changes.

3. In Paragraph 2, The operation of calculating the cost function for each of the aforementioned plurality of lanes is, An operation to calculate the first parameter based on the number of lane changes required to reach the above destination and the distance to the above destination. A method including 4. In Paragraph 2, The operation of calculating the cost function for each of the aforementioned plurality of lanes is, The operation of calculating the second parameter based on the distance between the vehicle and the vehicle ahead and the speed of the vehicle. A method including 5. In Paragraph 2, The operation of calculating the cost function for each of the aforementioned plurality of lanes is, The operation of calculating the third parameter based on the distance between the vehicle and the vehicle behind it and the relative speed of the vehicle behind it with respect to the vehicle. A method including 6. In Paragraph 2, The operation of calculating the cost function for each of the aforementioned plurality of lanes is, When the vehicle turns right, if the obstacle is located in the far right lane, the operation of calculating the fourth parameter based on the time the obstacle existed. Includes, The above obstacle is, A method including a stationary vehicle.

7. In Paragraph 2, The operation of calculating the cost function for each of the aforementioned plurality of lanes is, The operation of calculating the fifth parameter by applying a different penalty to the lane to be changed depending on whether the lane to be changed by the vehicle matches the driving path. A method including 8. In Paragraph 1, The above plurality of lanes are, The first lane and the second lane Including, The operation of determining the lane having the minimum cost among the above plurality of lanes as the target lane is, The operation of comparing the result value of the first cost function of the first lane and the result value of the second cost function of the second lane, and determining the lane corresponding to the cost function having the smaller result value as the target lane. A method including 9. In an electronic device for determining a lane, processor; and Memory that stores instructions Includes, The above instructions are executed individually or collectively by the processor, causing the electronic device, Calculate the cost function for each of the multiple lanes included in the road on which the vehicle is traveling, and Based on the above cost function, the lane having the minimum cost among the plurality of lanes is determined as the target lane, and The above cost function is, An electronic device that quantifies and represents driving factors occurring when the vehicle travels on a lane corresponding to the cost function.

10. In Paragraph 9, The above cost function is, One or more of the first to fifth parameters Includes, The above first parameter is, It concerns the cost representing the efficiency of the driving route to reach the destination, and The above second parameter is, This concerns the costs required to prevent a collision with a vehicle in front of the above-mentioned vehicle, and The above third parameter is, This concerns the costs required to prevent a collision with a vehicle behind the above-mentioned vehicle, and The above fourth parameter is, This relates to the cost required to avoid obstacles on the aforementioned driving path, and The above fifth parameter is, An electronic device concerning the costs required to prevent reckless lane changes.

11. In Paragraph 10, The above instructions are executed individually or collectively by the processor, causing the electronic device, An electronic device that calculates the first parameter based on the number of lane changes required to reach the destination and the distance to the destination.

12. In Paragraph 10, The above instructions are executed individually or collectively by the processor, causing the electronic device, An electronic device that calculates the second parameter based on the distance between the vehicle and the vehicle ahead and the speed of the vehicle.

13. In Paragraph 10, The above instructions are executed individually or collectively by the processor, causing the electronic device, An electronic device for calculating the third parameter based on the distance between the vehicle and the vehicle behind it and the relative speed of the vehicle behind it with respect to the vehicle.

14. In Paragraph 10, The above instructions are executed individually or collectively by the processor, causing the electronic device, When the vehicle turns right, if the obstacle is located in the far right lane, the fourth parameter is calculated based on the time the obstacle existed. The above obstacle is, Electronic device including a stationary vehicle.

15. In Paragraph 10, The above instructions are executed individually or collectively by the processor, causing the electronic device, An electronic device that calculates the fifth parameter by applying a different penalty to the lane to be changed depending on whether the lane to be changed by the vehicle matches the driving path.

16. In Paragraph 9, The above plurality of lanes are, The first lane and the second lane Including, The above instructions are executed individually or collectively by the processor, causing the electronic device, An electronic device that compares the output of a first cost function of the first lane and the output of a second cost function of the second lane, and determines the lane corresponding to the cost function having a smaller output as the target lane.

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