Title of Invention: EXPOSURE CONTROL DEVICE, EXPOSURE CONTROL METHOD, PROGRAM, IMAGING DEVICE, AND MOBILE BODY Abstract: The present technology relates to an exposure control device, an exposure control method, a program, an imaging device, and a mobile body that allow for appropriate exposure control. The exposure control device includes: a wave-detection unit that calculates a wave-detection value, in a captured image taken by an imaging unit, by assigning a smaller weight to an area that is predicted to go out of an angle of view of the imaging unit within a predetermined time; and an exposure control unit that performs exposure control of the imaging unit on the basis of the wave-detection value. The present technology can be applied to, for example, an imaging device or an imaging system provided in a mobile body such as a vehicle, a robot, or the like. Detailed Description: TECHNICAL FIELD The present technology relates to an exposure control device, an exposure control method, a program, an imaging device, and a mobile body, and particularly relates to an exposure control device, an exposure control method, a program, an imaging device, and a mobile body suitable for use in auto exposure. BACKGROUND ART Conventionally, there has been proposed defining a distant small frame in which a distant vehicle is expected to be running with respect to a distant road vanishing point in the driving direction of a subject vehicle, and performing exposure control of an in-vehicle camera on the basis of information regarding the brightness within the distant small frame (see Patent Document 1, for example). CITATION LIST Patent Document Patent Document 1: Japanese Patent Application Laid-Open No. 2017-5678 SUMMARY OF THE INVENTION Problems to be Solved by the Invention Meanwhile, for example, when the brightness of the surroundings abruptly changes near the entrance, exit, or the like of a tunnel, the exposure control of the in-vehicle camera may fail to be timely performed, causing a captured image to have blown-out highlights in a bright area or blocked-up shadows in a dark area. Patent Document 1 does not give consideration to measures against this problem. The present technology has been made in view of such circumstances, and is intended to achieve appropriate exposure control. Solutions to Problems An exposure control device according to a first aspect of the present technology includes: a wave-detection unit that calculates a wave-detection value, in a captured image taken by an imaging unit, by assigning a smaller weight to an area that is predicted to go out of an angle of view of the imaging unit within a predetermined time; and an exposure control unit that performs exposure control of the imaging unit on the basis of the wave-detection value. An exposure control method according to the first aspect of the present technology includes: calculating a wave-detection value, in a captured image taken by an imaging unit, by assigning a smaller weight to an area that is predicted to go out of an angle of view of the imaging unit within a predetermined time; and performing exposure control of the imaging unit on the basis of the wave-detection value. A program according to the first aspect of the present technology is configured to cause a computer to execute processes of: calculating a wave-detection value, in a captured image taken by an imaging unit, by assigning a smaller weight to an area that is predicted to go out of an angle of view of the imaging unit within a predetermined time; and performing exposure control of the imaging unit on the basis of the wave-detection value. An imaging device according to a second aspect of the present technology includes: an imaging unit; a wave-detection unit that calculates a wave-detection value, in a captured image taken by the imaging unit, by assigning a smaller weight to an area that is predicted to go out of an angle of view of the imaging unit within a predetermined time; and an exposure control unit that performs exposure control of the imaging unit on the basis of the wave-detection value. A mobile body according to a third aspect of the present technology includes: an imaging unit; a wave-detection unit that calculates a wave-detection value, in a captured image taken by the imaging unit, by assigning a smaller weight to an area that is predicted to go out of an angle of view of the imaging unit within a predetermined time; an exposure control unit that performs exposure control of the imaging unit on the basis of the wave-detection value; and a movement control unit that performs movement control on the basis of the captured image. In the first aspect and the second aspect of the present technology, a wave-detection value is calculated, in a captured image taken by an imaging unit, by assigning a smaller weight to an area that is predicted to go out of an angle of view of the imaging unit within a predetermined time, and exposure control of the imaging unit is performed on the basis of the wave-detection value. In the second aspect of the present technology, a wave-detection value is calculated, in a captured image taken by an imaging unit, by assigning a smaller weight to an area that is predicted to go out of an angle of view of the imaging unit within a predetermined time, and exposure control of the imaging unit is performed on the basis of the wave-detection value. In the third aspect of the present technology, a wave-detection value is calculated, in a captured image taken by an imaging unit, by assigning a smaller weight to an area that is predicted to go out of an angle of view of the imaging unit within a predetermined time, exposure control of the imaging unit is performed on the basis of the wave-detection value, and movement control is performed on the basis of the captured image. Effects of the Invention According to the first aspect or the second aspect of the present technology, exposure control can be appropriately performed. According to the third aspect of the present technology, exposure control can be appropriately performed. As a result, movement of a mobile body can be appropriately controlled. Note that the effects described above are not restrictive, and any of effects described in the present disclosure may be included. BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a block diagram illustrating an example configuration of a mobile body control system to which the present technology can be applied. FIG. 2 is a block diagram illustrating a first embodiment of an imaging system to which the present technology is applied. FIG. 3 is a flowchart for explaining an exposure control process performed by the imaging system in FIG. 2. FIG. 4 is a schematic diagram showing an example of a captured image. FIG. 5 is a diagram illustrating a first example of weights assigned to divided areas. FIG. 6 is a schematic diagram of an example of a captured image including blown-out highlights. FIG. 7 is a schematic diagram of an example of a captured image including blocked-up shadows. FIG. 8 is a diagram illustrating an example of lifetime. FIG. 9 is a diagram illustrating a second example of weights assigned to divided areas. FIG. 10 is a diagram illustrating an example of a parameter table. FIG. 11 is a diagram for explaining a parameter based on an image gradient. FIG. 12 is a block diagram illustrating a second embodiment of an imaging system to which the present technology is applied. FIG. 13 is a flowchart for explaining an exposure control process performed by the imaging system in FIG. 12. FIG. 14 is a diagram for explaining a first method for setting a wave-detection area. FIG. 15 is a diagram for explaining a second method for setting a wave-detection area. FIG. 16 is a diagram for explaining the second method for setting a wave-detection area. FIG. 17 is a diagram illustrating an example configuration of a computer. MODE FOR CARRYING OUT THE INVENTION A mode for carrying out the present technology will now be described. Descriptions are provided in the order mentioned below. 1. Example configuration of mobile body control system 2. First embodiment (example of using weighted average of brightness) 3. Second embodiment (example of setting wave-detection area) 4. Modifications 5. Others «1. Example Configuration of Mobile Body Control System» FIG. 1 is a block diagram illustrating an example configuration of general functions of a mobile body control system 100 to which the present technology is applied. The mobile body control system 100 is a system disposed in a mobile body 10 to perform various types of control over the mobile body 10. The mobile body 10 includes, for example, a mobile body that captures images of the surroundings while moving and performs processing using the captured images. Examples of the mobile body 10 include mobile bodies with passengers such as a vehicle, a motorcycle, a bicycle, a personal mobility, an airplane, a ship, a construction machine, an agricultural machine (tractor), and the like. In addition, examples of the mobile body 10 include mobile bodies without passengers such as a drone, a robot, and the like that are moved by remote operation or automatic control. Moreover, the mobile body 10 may be moved by, for example, direct operation, remote operation, or automatic control. The mobile body control system 100 includes an input unit 101, a data acquisition unit 102, a communication unit 103, mobile body internal equipment 104, an output control unit 105, an output unit 106, a drive system control unit 107, a drive system 108, a storage unit 109, and an autonomous movement control unit 110. The input unit 101, the data acquisition unit 102, the communication unit 103, the output control unit 105, the drive system control unit 107, the storage unit 109, and the autonomous movement control unit 110 are connected to one another via a communication network 111. The communication network 111 includes, for example, a controller area network (CAN), a local interconnect network (LIN), a local area network (LAN) such as IEEE 802.3, a communication network or a bus compliant with any standard such as FlexRay (registered trademark), a proprietary communication system that is not standardized, or the like. Note that the individual units in the mobile body control system 100 may be directly connected to one another without the communication network 111. Note that descriptions about the communication network 111 are hereinafter omitted in a case where the individual units in the mobile body control system 100 communicate with one another via the communication network 111. For example, communication between the input unit 101 and the autonomous movement control unit 110 via the communication network 111 is simply described as communication between the input unit 101 and the autonomous movement control unit 110. The input unit 101 includes a device used by a user to input various types of data, instructions, and the like. For example, the input unit 101 includes an operation device such as a touch panel, a button, a microphone, a switch, and a lever, and an operation device that can provide inputs by a method other than manual operation such as by sound, gesture, or the like. Furthermore, the input unit 101 may be, for example, a remote control device employing infrared rays or other radio waves, or an externally connected apparatus such as a mobile apparatus or a wearable apparatus supporting operation of the mobile body control system 100. The input unit 101 generates an input signal on the basis of data, an instruction, or the like input by the user, and supplies the input signal to the individual units in the mobile body control system 100. The data acquisition unit 102 includes various sensors or the like that acquire data to be used for processing in the mobile body control system 100 and supplies the acquired data to the individual units in the mobile body control system 100. For example, the data acquisition unit 102 includes various sensors for detecting the state and the like of the mobile body 10. Specifically, the data acquisition unit 102 includes, for example, a gyro sensor, an acceleration sensor, and an inertial measurement unit (IMU), as well as including sensors or the like for detecting an operation amount of an accelerator or other acceleration input, an operation amount of deceleration input, an operation amount of direction instruction input, the number of rotations, input/output energy, and a fuel amount of a driving device such as an engine or a motor, a torque amount of an engine, a motor, or the like, a rotation speed or torque of a wheel or joint, or the like. Furthermore, the data acquisition unit 102 includes, for example, various sensors for detecting information regarding the outside of the mobile body 10. Specifically, the data acquisition unit 102 includes, for example, an imaging device such as a time-of-flight (ToF) camera, a stereo camera, a monocular camera, an infrared camera, a polarized camera, and any other camera. Furthermore, the data acquisition unit 102 includes, for example, an environment sensor for detecting weather, climate, or the like, and a surrounding information detection sensor for detecting an object around the mobile body 10. The environment sensor includes, for example, a raindrop sensor, a fog sensor, a sunshine sensor, a snow sensor, and the like. The surrounding information detection sensor includes, for example, a laser ranging sensor, an ultrasonic sensor, a radar, a LiDAR (light detection and ranging, or laser imaging, detection, and ranging), a sonar, and the like. Moreover, the data acquisition unit 102 includes, for example, various sensors for detecting the current position of the mobile body 10. Specifically, the data acquisition unit 102 includes, for example, a GNSS receiver that receives a GNSS signal from a global navigation satellite system (GNSS) satellite, and the like. The communication unit 103 communicates with the mobile body internal equipment 104 and various apparatuses, servers, base stations, and the like outside the mobile body to transmit data supplied from the individual units in the mobile body control system 100 and supply received data to the individual units in the mobile body control system 100. Note that the communication protocol supported by the communication unit 103 is not particularly limited, and the communication unit 103 can support a plurality of types of communication protocols. For example, the communication unit 103 wirelessly communicates with the mobile body internal equipment 104 by a wireless LAN, Bluetooth (registered trademark), near-field communication (NFC), Wireless USB (WUSB), or the like. Furthermore, for example, the communication unit 103 performs wired communication with the mobile body internal equipment 104 by Universal Serial Bus (USB), High-Definition Multimedia Interface (HDMI) (registered trademark), Mobile High-Definition Link (MHL), or the like via a connection terminal (not illustrated) (and a cable, if necessary). Moreover, for example, the communication unit 103 communicates with an apparatus (for example, an application server or a control server) present on an external network (for example, the Internet, a cloud network, or an operator-specific network) via a base station or an access point. Furthermore, for example, the communication unit 103 communicates with a terminal present in the vicinity of the mobile body 10 (for example, a terminal of a pedestrian or store or a machine-type communication (MTC) terminal) using the peer-to-peer (P2P) technology. Moreover, for example, in a case where the mobile body 10 is a vehicle, the communication unit 103 performs V2X communication such as vehicle-to-vehicle communication, vehicle-to-infrastructure communication, vehicle-to-home (mobile body 10 to home) communication, vehicle-to-pedestrian communication, and the like. Furthermore, for example, the communication unit 103 includes a beacon receiving unit to receive radio waves or electromagnetic waves emitted from a radio station or the like installed on a road to acquire information regarding the current position, traffic congestion, roadblocks, a required time, or the like. The mobile body internal equipment 104 includes, for example, a mobile apparatus or a wearable apparatus possessed by a user, an information apparatus carried by or attached to the mobile body 10, a navigation device that searches for a route to any destination, and the like. The output control unit 105 controls the output of various types of information to the user or to the outside of the mobile body. For example, the output control unit 105 generates an output signal including at least either one of visual information (such as image data) or auditory information (such as audio data) and supplies the output signal to the output unit 106, thereby controlling the output of visual information and auditory information from the output unit 106. Specifically, for example, the output control unit 105 combines pieces of image data captured by different imaging devices in the data acquisition unit 102 to generate a bird's eye image, a panoramic image, or the like, and supplies an output signal including the generated image to the output unit 106. Furthermore, for example, the output control unit 105 generates sound data including a warning sound, a warning message, or the like about a hazard such as collision, contact, or entry into a danger area, and supplies an output signal including the generated sound data to the output unit 106. The output unit 106 includes a device capable of outputting visual information or auditory information to the user or to the outside of the mobile body. For example, the output unit 106 includes a display device, an instrument panel, an audio speaker, a headphone, a wearable device such as a glasses-type display worn on the user, a projector, a lamp, and the like. The display device included in the output unit 106 may not only be a device having a general display but also be, for example, a device that displays visual information in the driver's field of view such as a head-up display, a see-through display, a device with an augmented reality (AR) display function, or the like. Note that the output control unit 105 and the output unit 106 are non-essential components for the autonomous movement processing, and thus may be omitted as necessary. The drive system control unit 107 controls the drive system 108 by generating various control signals and supplying the control signals to the drive system 108. Furthermore, the drive system control unit 107 supplies control signals to the individual units other than the drive system 108 as necessary to make, for example, a notification of the control state of the drive system 108. The drive system 108 includes various devices involved in the drive system of the mobile body 10. For example, the drive system 108 includes a servo motor that is disposed at each of joints in the four legs and is capable of accepting specified angle and torque, a motion controller that decomposes the motion of movement of the robot itself and replaces the motion with motions of the four legs, and a feedback control device supported by sensors in each motor and sensors on the soles of the feet. In another example, the drive system 108 includes motors with four to six airframe upward propellers and a motion controller that decomposes the motion of movement of the robot itself and replaces the motion with the rotation amount of each motor. In still another example, the drive system 108 includes a driving force generation device for generating a driving force for an internal combustion engine, a driving motor, or the like, a driving force transmission mechanism for transmitting a driving force to a wheel, a steering mechanism for adjusting a steering angle, a braking device for generating a braking force, an antilock brake system (ABS), electronic stability control (ESC), an electric power steering device, and the like. The storage unit 109 includes, for example, a read only memory (ROM), a random access memory (RAM), a magnetic storage device such as a hard disc drive (HDD), a semiconductor storage device, an optical storage device, a magneto-optical storage device, and the like. The storage unit 109 stores various programs, data, and the like used by the individual units in the mobile body control system 100. For example, the storage unit 109 stores map data including three-dimensional high-precision maps such as dynamic maps, global maps covering a broader area with lower precision than high-precision maps, local maps including information regarding surroundings of the mobile body 10, and the like. The autonomous movement control unit 110 performs control related to autonomous movement such as automated driving, driving assistance, or the like. Specifically, the autonomous movement control unit 110 performs, for example, coordinated control for the purpose of achieving functions of avoiding collision of, or mitigating impact on, the mobile body 10, following movement based on the distance between mobile bodies, moving the mobile body at constant speed, or warning of collision of the mobile body 10. Furthermore, the autonomous movement control unit 110 performs, for example, coordinated control for the purpose of autonomous movement and the like for autonomously moving without relying on user operations. The autonomous movement control unit 110 includes a detecting unit 131, a self-position estimating unit 132, a situation analyzing unit 133, a planning unit 134, and a motion control unit 135. The detecting unit 131 detects various types of information necessary for controlling the autonomous movement. The detecting unit 131 includes a mobile body external information detecting unit 141, a mobile body internal information detecting unit 142, and a mobile body state detecting unit 143. The mobile body external information detecting unit 141 performs a process of detecting information regarding the outside of the mobile body 10 on the basis of data or signals from the individual units in the mobile body control system 100. For example, the mobile body external information detecting unit 141 performs processes of detecting, recognizing, and tracking an object around the mobile body 10 and a process of detecting the distance to the object. Objects to be detected include, for example, another mobile body, a person, an obstacle, a structure, a road, a traffic signal, a traffic sign, a road marking, and the like. Furthermore, the mobile body external information detecting unit 141 performs, for example, a process of detecting the ambient environment around the mobile body 10. The ambient environment to be detected includes, for example, weather, temperature, humidity, brightness, road surface condition, and the like. The mobile body external information detecting unit 141 supplies data indicating results of the detection process to the self-position estimating unit 132, a map analysis unit 151 and a situation recognizing unit 152 in the situation analyzing unit 133, and to the motion control unit 135 and the like. The mobile body internal information detecting unit 142 performs a process of detecting information regarding the inside of the mobile body on the basis of data or signals from the individual units in the mobile body control system 100. For example, the mobile body internal information detecting unit 142 performs processes of authenticating and recognizing the driver, detecting the state of the driver, detecting a passenger, detecting the internal environment in the mobile body, and the like. The state of the driver to be detected includes, for example, physical condition, wakeful level, concentration level, fatigue level, line-of-sight direction, and the like. The mobile body internal environment to be detected includes, for example, temperature, humidity, brightness, smell, and the like. The mobile body internal information detecting unit 142 supplies data indicating results of the detection process to the situation recognizing unit 152 in the situation analyzing unit 133 and to the motion control unit 135 and the like. The mobile body state detecting unit 143 performs a process of detecting the state of the mobile body 10 on the basis of data or signals from the individual units in the mobile body control system 100. The state of the mobile body 10 to be detected includes, for example, velocity, acceleration, angular velocity, steering angle, presence or absence of abnormality and details of the abnormality, the state of driving operation, position and tilt of power seat, door locked or unlocked, states of other devices installed in the mobile body, and the like. The mobile body state detecting unit 143 supplies data indicating results of the detection process to the situation recognizing unit 152 in the situation analyzing unit 133 and to the motion control unit 135 and the like. The self-position estimating unit 132 performs a process of estimating the position, the posture, and the like of the mobile body 10 on the basis of data or signals from the individual units in the mobile body control system 100 including the mobile body external information detecting unit 141 and the situation recognizing unit 152 in the situation analyzing unit 133, and the like. Furthermore, the self-position estimating unit 132 generates, if necessary, a local map used for estimating the self-position (hereinafter referred to as a map for self-position estimation). The map for self-position estimation may be, for example, a high-precision map employing a technology such as simultaneous localization and mapping (SLAM). The self-position estimating unit 132 supplies data indicating results of the estimation process to the map analysis unit 151 in the situation analyzing unit 133 and to the situation recognizing unit 152 and the like. Furthermore, the self-position estimating unit 132 causes the storage unit 109 to store the map for self-position estimation. The situation analyzing unit 133 performs a process of analyzing the situations of the mobile body 10 and its surroundings. The situation analyzing unit 133 includes the map analysis unit 151, the situation recognizing unit 152, and a situation predicting unit 153. The map analysis unit 151 performs a process of analyzing various maps stored in the storage unit 109 while using, if necessary, data or signals from the individual units in the mobile body control system 100 including the self-position estimating unit 132, the mobile body external information detecting unit 141, and the like to construct a map that includes information necessary for the autonomous movement processing. The map analysis unit 151 supplies the constructed map to the situation recognizing unit 152 and the situation predicting unit 153, and to a route planning unit 161, an action planning unit 162, and a motion planning unit 163 in the planning unit 134, and the like. The situation recognizing unit 152 performs a process of recognizing situations of and around the mobile body 10 on the basis of data or signals from the individual units in the mobile body control system 100 including the self-position estimating unit 132, the mobile body external information detecting unit 141, the mobile body internal information detecting unit 142, the mobile body state detecting unit 143, the map analysis unit 151, and the like. For example, the situation recognizing unit 152 performs processes of recognizing the situation of the mobile body 10, the situation around the mobile body 10, the situation of the driver of the mobile body 10, and the like. Furthermore, the situation recognizing unit 152 generates, if necessary, a local map used for recognizing situations around the mobile body 10 (hereinafter referred to as a map for situation recognition). The map for situation recognition may be, for example, an occupancy grid map, a lane map, or a point cloud map. The situation of the mobile body 10 to be recognized includes, for example, the position, posture, movement (for example, velocity, acceleration, moving direction, and the like) of the mobile body 10, and presence or absence of abnormality, details of the abnormality, and the like. The situation around the mobile body 10 to be recognized includes, for example, the type and position of a stationary object therearound, the type, position, and movement of a moving object therearound (for example, velocity, acceleration, moving direction, and the like), the arrangement of roads therearound and road surface conditions, and the ambient weather, temperature, humidity, brightness, and the like. The state of the driver to be recognized includes, for example, physical condition, wakeful level, concentration level, fatigue level, changes in line-of-sight, driving operation, and the like. The situation recognizing unit 152 supplies data indicating the result of the recognition process (including the map for situation recognition, if necessary) to the self-position estimating unit 132, the situation predicting unit 153, and the like. Furthermore, the situation recognizing unit 152 causes the storage unit 109 to store the map for situation recognition. The situation predicting unit 153 performs a process of predicting the situations of and around the mobile body 10 on the basis of data and signals from the individual units in the mobile body control system 100 including the map analysis unit 151, the situation recognizing unit 152, and the like. For example, the situation predicting unit 153 performs processes of predicting the situation of the mobile body 10, the situation around the mobile body 10, the situation of the driver, and the like. The situation of the mobile body 10 to be predicted includes, for example, the behavior of the mobile body 10, any occurrence of abnormality, a possible travel distance, and the like. The situation around the mobile body 10 to be predicted includes, for example, the behavior of a moving object around the mobile body 10, a change in the state of a signal, a change in the environment such as weather, and the like. The situation of the driver to be predicted includes, for example, the behavior, physical condition, and the like of the driver. The situation predicting unit 153 supplies data indicating the result of the prediction process along with data from the situation recognizing unit 152 to the route planning unit 161, the action planning unit 162, and the motion planning unit 163 in the planning unit 134, and the like. The route planning unit 161 plans a route to the destination on the basis of data or signals from the individual units in the mobile body control system 100 including the map analysis unit 151, the situation predicting unit 153, and the like. For example, the route planning unit 161 sets a route from the current position to the specified destination on the basis of the global map. Furthermore, for example, the route planning unit 161 changes the route, as appropriate, on the basis of the conditions including traffic congestion, traffic accident, roadblocks, construction work, the driver's physical condition, and the like. The route planning unit 161 supplies data indicating the planned route to the action planning unit 162 and the like. The action planning unit 162 plans an action of the mobile body 10 for safely moving along the route planned by the route planning unit 161 within a planned time on the basis of data or signals from the individual units in the mobile body control system 100 including the map analysis unit 151, the situation predicting unit 153, and the like. For example, the action planning unit 162 creates plans including start, stop, traveling direction (for example, moving forward, moving backward, turning left, turning right, turning in some other direction, and the like), moving speed, overtaking, and the like. The action planning unit 162 supplies data indicating the planned action of the mobile body 10 to the motion planning unit 163 and the like. The motion planning unit 163 plans motions of the mobile body 10 for achieving the action planned by the action planning unit 162 on the basis of data or signals from the individual units in the mobile body control system 100 including the map analysis unit 151, the situation predicting unit 153, and the like. For example, the motion planning unit 163 plans acceleration, deceleration, movement tracks, and the like. The motion planning unit 163 supplies data indicating the planned motions of the mobile body 10 to the motion control unit 135 and the like. The motion control unit 135 controls motions of the mobile body 10. More specifically, the motion control unit 135 performs a process of detecting an emergency such as collision, contact, entry into a danger area, abnormality of the driver, abnormality of the mobile body 10, and the like on the basis of the result of detection by the mobile body external information detecting unit 141, the mobile body internal information detecting unit 142, and the mobile body state detecting unit 143. Upon detection of the occurrence of an emergency, the motion control unit 135 plans a motion of the mobile body 10 for avoiding the emergency such as quick stop, quick turning, or the like. Furthermore, the motion control unit 135 performs acceleration and deceleration control so that the mobile body 10 can achieve the motion planned by the motion planning unit 163. For example, the motion control unit 135 calculates a control target value for a driving force generating device or a braking device to achieve the planned acceleration, deceleration, or quick stop, and supplies a control command indicating the calculated control target value to the drive system control unit 107. Moreover, the motion control unit 135 performs directional control so that the mobile body 10 can achieve the motion planned by the motion planning unit 163. For example, the motion control unit 135 calculates a control target value for a steering mechanism to achieve the movement track or quick turn planned by the motion planning unit 163 and supplies a control command indicating the calculated control target value to the drive system control unit 107. Note that descriptions are provided below with examples in which the mobile body 10 is a vehicle in most cases. «2. First Embodiment» A first embodiment of the present technology will now be described with reference to FIGS. 2 to 11. Note that the first embodiment mainly relates to processing by the data acquisition unit 102 in the mobile body control system 100 in FIG. 1. <Example Configuration of Imaging System> FIG. 2 is a block diagram illustrating an example configuration of an imaging system 201, which represents the first embodiment of the present technology. The imaging system 201 is a system that takes images of surroundings of the mobile body 10. The imaging system 201 includes an imaging unit 211 and a control unit 212. Note that the imaging system 201 may include a single device (an imaging device, for example) or include a plurality of devices. In the latter case, for example, the imaging unit 211 and the control unit 212 may be respectively included in different devices (for example, an imaging device and an exposure control device), or the imaging unit 211 and part of the control unit 212 may be included in one device (for example, an imaging device) and the rest of the control unit 212 may be included in a different device (for example, an exposure control device). The imaging unit 211 takes images of surroundings of the mobile body 10. The imaging unit 211 supplies an image obtained as a result of the imaging (hereinafter referred to as a captured image) to the detecting unit 131 and the self-position estimating unit 132 in the mobile body control system 100 and to a weight setting unit 231 in a wave-detection unit 221 in the control unit 212 and the like. Furthermore, the imaging unit 211 adjusts the amount of exposure by adjusting the exposure time (shutter speed) of an imaging element (not illustrated), the gain (sensitivity) of the imaging element, and the aperture size on the basis of a control signal from a control signal generating unit 244. The control unit 212 performs exposure control and the like of the imaging unit 211. The control unit 212 includes the wave-detection unit 221 and an exposure control unit 222. The wave-detection unit 221 detects a wave-detection value based on brightness levels of a captured image and supplies a wave-detection signal indicating the wave-detection value to an error detecting unit 241 in the exposure control unit 222. The wave-detection unit 221 includes the weight setting unit 231 and a wave-detection value calculating unit 232. As described later, the weight setting unit 231 divides a captured image into a plurality of divided areas and assigns a weight to each divided area. The weight setting unit 231 supplies the captured image and data indicating the weights of the individual divided areas to the wave-detection value calculating unit 232. The wave-detection value calculating unit 232 calculates a wave-detection value on the basis of the brightness levels and weights of the individual divided areas in the captured image. The wave-detection value calculating unit 232 supplies a wave-detection signal indicating the wave-detection value to the error detecting unit 241 in the exposure control unit 222. The exposure control unit 222 performs exposure control of the imaging unit 211 on the basis of the wave-detection signal. The exposure control unit 222 includes the error detecting unit 241, an exposure amount setting unit 242, a control method setting unit 243, and the control signal generating unit 244. The error detecting unit 241 detects an error of the wave-detection value detected by the wave-detection unit 221 with respect to a target value and supplies data indicating the detected error to the exposure amount setting unit 242. The exposure amount setting unit 242 sets a target value of exposure amount for the imaging unit 211 on the basis of the error in the wave-detection value. The exposure amount setting unit 242 supplies data indicating the target value of the exposure amount to the control method setting unit 243. The control method setting unit 243 sets a method for controlling the exposure in the imaging unit 211 so that the exposure amount in the imaging unit 211 reaches the target value. The control method setting unit 243 supplies the target value of exposure amount and data indicating the method for controlling the exposure to the control signal generating unit 244. The control signal generating unit 244 generates a control signal for controlling the exposure in the imaging unit 211 in accordance with the designated method for controlling the exposure so that the exposure amount reaches the target value, and supplies the generated control signal to the imaging unit 211. <Exposure Control Process> Referring to the flowchart in FIG. 3, the following describes an exposure control process performed by the imaging system 201. For example, the process is started when the imaging system 201 is powered on and is exited when the imaging system 201 is powered off. In step S1, the imaging unit 211 takes images of surroundings of the mobile body 10. The imaging unit 211 supplies the captured image obtained by the imaging to the detecting unit 131, the self-position estimating unit 132, the weight setting unit 231, and the like. The mobile body external information detecting unit 141 in the detecting unit 131 (FIG. 1) detects, for example, feature points in the captured image and the position (distance and direction) of each feature point with respect to the mobile body 10. Note that any method can be used for detecting a feature point. Furthermore, the mobile body external information detecting unit 141 detects, for example, the position, type, and the like of each subject in the captured image. Note that any method can be used for detecting a subject such as, for example, semantic segmentation, human body detection, vehicle detection, or the like. Moreover, the mobile body external information detecting unit 141 detects, for example, the movement (for example, velocity, moving direction, and the like) of each subject in the captured image. Note that any method can be used for detecting the movement of a subject. The self-position estimating unit 132 estimates the self-position of the mobile body 10 on the basis of the captured image and others. Note that the following describes a case where the image that has been taken is a captured image P1 schematically shown in FIG. 4, with specific examples provided as appropriate. The captured image P1 is an image captured in front of the mobile body 10, showing the sky, a road surface ahead, other vehicles on the road, and buildings, trees, and the like on both sides of the road. In step S2, the weight setting unit 231 acquires information regarding the mobile body 10 and its surroundings. For example, the weight setting unit 231 acquires, from the mobile body external information detecting unit 141, data indicating detection results including feature points in the captured image, the position (distance and direction) of each feature point with respect to the mobile body 10, and the position, type, movement, and the like of each subject in the captured image. Furthermore, for example, the weight setting unit 231 acquires, from the mobile body state detecting unit 143 in the detecting unit 131 (FIG. 1), data indicating detection results including the velocity, angular velocity, and the like of the mobile body 10. Moreover, for example, the weight setting unit 231 acquires, from the self-position estimating unit 132, data indicating the result of estimating the self-position of the mobile body 10. In step S3, the weight setting unit 231 assigns a weight to each divided area in the captured image. Specifically, the weight setting unit 231 divides the captured image into a plurality of divided areas. Then, the weight setting unit 231 assigns a weight to each divided area as described later in detail. The weight setting unit 231 supplies the captured image and data indicating the weights of the individual divided areas to the wave-detection value calculating unit 232. In step S4, the wave-detection value calculating unit 232 calculates a wave-detection value on the basis of the brightness levels and weights of the individual divided areas in the captured image. The wave-detection value calculating unit 232 supplies a wave-detection signal indicating the wave-detection value to the error detecting unit 241. Here, a specific example of a method for calculating the wave-detection value in step S3 and step S4 is described with reference to FIGS. 5 to 11. <First Method for Calculating Wave-Detection Value> First, the following describes a first method for calculating the wave-detection value with reference to FIGS. 5 to 9. For example, as illustrated in FIG. 5, the weight setting unit 231 divides the captured image P1 into n (48 in this example) rectangular divided areas i (i=1 to n) having the same size, and assigns a weight wi to each divided area i. The number in each divided area i in FIG. 5 indicates the weight wi of the divided area i. In this example, the weight wi of every divided area is set to 1. The wave-detection value calculating unit 232 calculates, as the wave-detection value, the weighted average of brightness levels of the individual divided areas i in accordance with the following equation (1). [ Mathematical   1 ] wave  -  detection   value = ∑ i = 1 n  w i * x i ∑ i = 1 n  w i ( 1 ) Note that xi represents the average xi of brightness levels of individual pixels in the divided area i (hereinafter referred to as average brightness xi). Here, the example in FIG. 5 shows that the weight wi of every divided area i is set to 1. Then, substituting 1 into the weight wi in the equation (1) gives the following equation (2). [ Mathematical   2 ] wave  -  detection   value = ∑ i = 1 n  x i n ( 2 ) That is, if the weight wi of every divided area i is set to 1, the wave-detection value is equal to the average of the average brightness levels xi of individual divided areas i. In other words, the wave-detection value is equal to the simple average of brightness levels of individual pixels in the captured image P1. However, if the wave-detection value is set to the simple average of brightness levels of individual pixels in a captured image, the exposure in the imaging unit 211 may not always be controlled appropriately in a case where the brightness around the mobile body 10 abruptly changes. That is, since exposure control is usually performed on the basis of a wave-detection value based on the captured image taken earlier by a predetermined number of frames or by a predetermined time, the exposure control may fail to quickly follow the change in ambient brightness when the ambient brightness abruptly changes. For example, at the time of moving from a dark place to a bright place near the exit or the like of a tunnel or a forest, the exposure control may fail to be performed in time, causing a captured image to have blown-out highlights in bright areas. For example, FIG. 6 schematically shows a captured image P2 taken near the exit of a forest. For example, an area Al in the captured image P2 is caused to have blown-out highlights near the exit of the forest and in a bright area ahead of the exit. Therefore, the situation outside the forest cannot be accurately recognized, which may decrease the accuracy of the self-position estimation, obstacles recognition, and the like. Furthermore, for example, at the time of moving from a bright place to a dark place near the entrance or the like of a tunnel or a forest, the exposure control may fail to be performed in time, causing a captured image to have blocked-up shadows in dark areas. For example, FIG. 7 schematically shows a captured image P3 taken near the entrance of a tunnel. For example, an area A2 in the captured image P3 is caused to have blocked-up shadows in a dark area inside the tunnel. Therefore, the situation inside the tunnel cannot be accurately recognized, which may cause troubles with the self-position estimation, obstacles recognition, and the like. To address this problem, first, the weight setting unit 231 predicts a lifetime ti of each divided area i. The lifetime ti refers to a period of time during which a divided area i (a subject in the divided area) continues to be shown in the captured image on and after a reference time serving as a basis for predicting the lifetime. In other words, the lifetime ti refers to a period of time during which a divided area i (a subject in the divided area) remains within the angle of view of the imaging unit 211 on and after the reference time. More specifically, the lifetime refers to, for example, a period of time from the time point (reference time) at which the prediction of the lifetime starts to the time point at which a divided area i (a subject in the divided area) goes out of the angle of view of the imaging unit 211 and no longer appears in the captured image. For example, the weight setting unit 231 sets a representative feature point pi in each divided area i in a captured image. In this process, in a case where a divided area i has only one feature point, the weight setting unit 231 identifies the feature point as the representative feature point pi. On the other hand, in a case where a plurality of feature points is present in a divided area i, the weight setting unit 231 identifies one of the feature points as the representative feature point pi. For example, the weight setting unit 231 selects the subject having the largest area in the divided area i or the most important subject in the divided area i. Here, the most important subject refers to a subject that most highly needs to be recognized, such as a person, a vehicle, a sign, or the like. Then, as the representative feature point pi, the weight setting unit 231 identifies, for example, the feature point having the largest feature amount among the feature points of the selected subject. Alternatively, for example, the weight setting unit 231 identifies, as the representative feature point pi, the feature point having the largest feature amount in the divided area i or the feature point closest to the center of the divided area i without regard to subjects. Then, the weight setting unit 231 predicts the lifetime ti of the divided area i on the basis of, for example, the velocity and moving direction of the mobile body 10 and the distance and direction of the representative feature point pi from the mobile body 10. For example, assuming that the mobile body 10 continues to move at the current velocity in the current moving direction, the weight setting unit 231 predicts the time when the representative feature point pi goes out of the captured image (the time when the representative feature point goes out of the angle of view of the imaging unit 211). The weight setting unit 231 identifies the time period from the current time to the predicted time as the lifetime ti of the divided area i. FIG. 8 shows examples of the lifetime of each point in the captured image P1 in a case where the mobile body 10 is moving in the arrow direction. The numerical value below each black dot in the figure indicates the lifetime of each point. In the example, a point on a subject closer to the mobile body 10
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