Abstract: Systems and methods for operating drones in proximity to objects are disclosed herein. An example method includes determining a change in drone, flight status that involves a rotor of the drone being active, determining presence of a mobile device within a designated clearance area established around the drone, preventing the drone from landing, providing a warning message to a user of the mobile device to clear away from the designated clearance area, detecting that the mobile device and the user are not within the designated clearance area, and causing the drone to land.

Abstract: An autonomous controller, a system including the same, and a method thereof include a processor that detects a target object attempting to cut in at a low speed during autonomous driving and that performs response control. The controller, system, and method include a storage storing data and an algorithm for detecting the target object and performing the response control. The processor calculates a final distance value on the basis of a point tracking a distance between a host vehicle and the target object and compares the final distance value with a predetermined threshold to determine whether the target object cuts in.

Abstract: In a vehicle control apparatus, a controller for controlling a travelling of a vehicle is configured to obtain attribute information about at least one occupant from reservation information, the reservation information including information about the at least one occupant who has made a reservation for the vehicle, and set a travelling characteristic of the vehicle based on the attribute information about at least one occupant.

Abstract: An autonomous work system includes a first work machine, a plurality of second work machines having different functions, a setting device that stores work schedule information indicating work schedule content, performance of the first work machine, and performance of the plurality of second work machines, and a terminal. The first work machine acquires a state of work performed by its own device and transmits detection result information indicating the acquired state of work to the setting device. The setting device discriminates whether additional work is required based on the detection result information and the work schedule information, and in a case where the additional work is required, selects the second work machine, and transmits additional work information including work content for the second work machine and information relating to the second work machine to at least one of the terminal and the second work machine.

Abstract: An automatic driving system includes an electronic control device configured to: detect a driving operation input amount during an automatic driving control for a vehicle; determine whether the driver is able to start manual driving during the automatic driving control for the vehicle; output a signal for performing switching from automatic driving to the manual driving based on a result of a comparison between the driving operation input amount and a driving switching threshold that is a threshold for the switching from the automatic driving to the manual driving; set the driving switching threshold to a first driving switching threshold when it is determined that the driver is able to start the manual driving; and set the driving switching threshold to a second driving switching threshold exceeding the first driving switching threshold when it is determined that the driver is not able to start the manual driving.

Abstract: Exemplary implementations may: obtain passenger information related to a passenger that is relevant to an upcoming medical appointment; store such passenger information; and transmit such passenger information wirelessly to a caregiver with which the upcoming medical appointment is scheduled. Exemplary implementation also may: generate output signals conveying passenger information; provide one or more automated robotic assistants; determine the passenger information; determine necessity of deployment of the one or more automated robotic assistants; and deploy, based on the necessity of deployment, the one or more automated robotic assistants.

Abstract: A system and method for an autonomous vehicle to perform an autonomous trip. A mobile communication device establishes a connection with an autonomous vehicle. The mobile communication device transmits a request for the autonomous vehicle to perform an autonomous trip. The autonomous trip includes the autonomous vehicle traveling from a first location to a second location without operator input. The autonomous trip is to be initiated by the autonomous vehicle based on the reception of the request.

Abstract: Control of a mobile device is transferred to and from an operator. In one aspect, a specification for triggering manual control of the mobile device is accessed. A location is identified within a geographic region that exhibits characteristics defined by the specification. The location is represented in a navigation map and is associated with an operator trigger. As the mobile device approaches the location, a request for manual control is provided to the operator based on the operator trigger, and manual control is initiated.

Abstract: A method includes receiving a video signal that comprises a time series of images of a face of a human, wherein the images in the time series of images comprise a set of landmark points in the face, applying tracking processing to the video signal to reveal variations over time of at least one image parameter at the set of landmark points in the human face, generating a set of variation signals indicative of variations revealed at respective landmark points in the set of landmark points, applying processing to the set of variation signals, the processing comprising artificial neural network processing to produce a reconstructed PhotoPletysmoGraphy (PPG) signal, and estimating a heart rate variability of a variable heart rate of the human as a function of the reconstructed PPG signal.

Abstract: Methods and systems herein relate to unmanned aerial vehicles (UAVs) avoiding collisions by interacting with servers. Some embodiments of a method include receiving, by an unmanned aircraft system (UAS) traffic management (UTM) server one or more intended trajectories from one or more UAVs; determining, by the UTM server one or more conflicts based on the intended trajectories intersecting over a region monitored by the UTM server; and communicating, by the UTM server the one or more conflicts, the communicating includes assigning a value to each of a plurality of three-dimensional (3D) grid cells representing the region monitored by the UTM server, each value representative of a potential for conflict associated with a grid cell; and transmitting, to the one or more UAVs, value data associated with the plurality of grid cells.

Abstract: A waste recycling system with an automated dumpster includes a main body and the main body includes a main control module. The main control module includes a main control unit, and is electrically connected to a dumpster module. The dumpster module includes a dumpster and the dumpster includes a sub-control module. The sub-control module includes a sub-control unit. The sub-control unit is electrically connected to a power unit and a scanning unit. The power unit is used to drive the dumpster and the scanning unit is disposed at the front end of the dumpster to receive signals. The sub-control unit also includes guiding units. The guiding unit is disposed on the transporting path of the dumpster. By the scanning unit, the scanned signal is transmitted back to the sub-control unit to control the dumpster moving automatically.

Abstract: Described herein are systems and methods that improve the success rate of relocalization and eliminate the ambiguity of false relocalization by exploiting motions of the sensor system. In one or more embodiments, during a relocalization process, a snapshot is taken using one or more visual sensors and a single-shot relocalization in a visual map is implemented to establish candidate hypotheses. In one or more embodiments, the sensors move in the environment, with a movement trajectory tracked, to capture visual representations of the environment in one or more new poses. As the visual sensors move, the relocalization system tracks various estimated localization hypotheses and removes false ones until one winning hypothesis. Once the process is finished, the relocalization system outputs a localization result with respect to the visual map.

Abstract: Lane configuration of a lane on which an ADV is driving and a current speed of the ADV are determined. A nudge space is determined based on the lane configuration, the current speed, and a vehicle width of the ADV. Path planning is performed to generate a path to nudge an obstacle, in response to the determining that the nudge space is greater than a predetermined threshold nudge space. The ADV is controlled to drive autonomously according to the planned path to nudge the obstacle.

Abstract: An obstacle avoidance method for a robot arm is provided, including a modeling step, a collecting and evaluating coordinates step, an obtaining control parameter step, an establishing an occupation function step, and a finding an obstacle avoiding posture step. The present invention pre-stores the data obtained in performing the modeling step, the step of collecting and evaluating coordinates, the step of obtaining control parameter, and the step of establishing the occupation function into a database, thereby allowing the robot arm to quickly evaluate whether a collision behavior will occur in subsequent execution of a task. If a collision will occur, the robot arm executes the step of the finding the obstacle avoiding posture to dodge obstacles. The invention uses a non-contact approach for anti-collision design, which can improve the shortcomings faced by the existing contact type anti-collision design.

Abstract: A method for assignment of vehicle control includes receiving route data indicating a route between a starting location of a vehicle and a destination location, and determining an optimal vehicle configuration for the route based on a target vehicle speed and a hybrid torque split. The method further includes receiving a driver requested torque value and determining a passive pedal torque value based on the route data and vehicle powertrain data. The method further includes selectively assigning control of the vehicle to a vehicle system or to a driver of the vehicle based on the driver requested torque value and the passive pedal torque value.

Abstract: A centralized hub system for improving automatic waste transport and collection using a self-driving robot, which allows for self-driving and efficient collection of waste in densely populated areas, such as apartment complexes and residential neighborhoods, and areas with a floating population by using robots with built-in artificial intelligence software and hardware and self-driving waste collection and driving functions and an integrated management server for monitoring these robots, and which helps to put information together in this process and use it as base data for the efficient operation of future waste policies and the corresponding systems. The centralized hub system for improving automatic waste transport and collection using a self-driving robot comprises self-driving inlet robots, an integrated management server, and a self-driving vehicle robot.

Abstract: Systems and methods for agricultural lane following are described. For example, a method includes accessing range data captured using a distance sensor connected to a vehicle and/or image data captured using an image sensor connected to a vehicle; detecting a crop row based on the range data and/or the image data to obtain position data for the crop row; determining, based on the position data for the crop row, a yaw and a lateral position of the vehicle with respect to a lane bounded by the crop row; and based on the yaw and the lateral position, controlling the vehicle to move along a length of the lane bounded by the crop row.

Abstract: An approach is provided for an unknown moving object detection system. The approach, for instance, involves capturing a plurality of unknown object events indicating an unknown object detected by one or more computer vision systems. The approach also involves clustering the plurality of unknown object events into a plurality of clusters based on one or more clustering parameters. The approach further involves selecting at least one cluster of the plurality of clusters based on a selection criterion. The approach further involves determining at least one operating scenario for the one or more computer vision systems based on a combination of the one or more clustering parameters associated with the selected at least one cluster.

Abstract: Methods, systems, and apparatuses related to autonomous vehicle object detection are described. A method can include receiving, by an autonomous vehicle, an indication that the autonomous vehicle has entered a network coverage zone generated by a base station and performing an operation to reallocate computing resources between a plurality of different types of memory devices associated with the autonomous vehicle in response to receiving the indication. The method can further include capturing, by the autonomous vehicle, data corresponding to an unknown object disposed within a sight line of the autonomous vehicle and performing, using the reallocated computing resources, an operation involving the data corresponding to the unknown object to classify the unknown object.

Abstract: The disclosure relates to an automated parking assist system for parking a vehicle in a parking spot, comprising a controller configured to handover drive control from a user to the automated parking assist system; and to start an automated parking procedure; wherein the controller is configured to initiate the handover as the vehicle approaches the parking spot, and to finish the handover before the vehicle reaches the parking spot.

Abstract: A moving body control apparatus includes a cancel control section performing control to cancel a lane change when a first cancel condition and a second cancel condition for cancelling the lane change are satisfied. When the first cancel condition is satisfied with the grip of an occupant on a manipulator being a prescribed level or greater, if a distance in a vehicle width direction between a moving body and a lane marker is a first distance threshold value or greater, the cancel control section judges that the second cancel condition is satisfied and cancels the lane change, and when the first cancel condition is satisfied with the grip being less than the prescribed level, if the distance is not less than a second distance threshold value greater than the first distance threshold value, the cancel control section judges that the second cancel condition is satisfied and cancels the lane change.

Abstract: A lane detection system for a vehicle includes at least one sensor for sensing lane markers and objects in the vicinity of a host vehicle, a driver interface in the host vehicle, and a controller having control logic. The control logic receives signals from the at least one sensor, determines a present lane of travel based on the sensor signals received, determines that a time that the host vehicle has been in the present lane of travel meets or exceeds a predetermined time, and transmits an alert signal to the driver interface in response to the time meeting or exceeding the predetermined time.

Abstract: A vehicle controller device including: a communication section configured to perform communication between an operation device external to a vehicle and another vehicle; a memory; and a processor that is coupled to the memory, the processor being configured to: acquire peripheral information regarding a periphery of the vehicle from a peripheral information detection section, generate a travel plan for the vehicle based on the peripheral information of the vehicle, acquire operation information to operate the vehicle from the operation device, control autonomous driving in which the vehicle travels based on the generated travel plan and also control remote driving in which the vehicle travels based on the acquired operation information, acquire peripheral information from the other vehicle in a case in which the processor is unable to acquire peripheral information, and hand over operation authority to the operation device when peripheral information is being acquired by the processor.

Abstract: Aspects and implementations of the present disclosure relate to modeling of positional uncertainty of moving objects using precomputed polygons, for example, for the purposes of computing autonomous vehicle (AV) trajectories. An example method includes: receiving, by a data processing system of an AV, data descriptive of an agent state of an object; generating a polygon representative of the agent state; identifying extreme vertices of the polygon along a longitudinal axis parallel to a heading direction of the object or along a lateral axis orthogonal to the heading direction; and applying, based on the extreme vertices, at least one expansion transformation to the polygon along the longitudinal axis or the lateral axis to generate a precomputed polygon.

Abstract: When there are a plurality of routes to one parking space, automatic parking cannot be performed on a route with short parking time. A route candidate generation unit 301 changes a reference vehicle speed and a route shape, and searches for a route from a parking start position to a parking target position. The route passage time calculation unit 302 calculates, for each route candidate, the time required to pass through the route based on the reference vehicle speed and the length of the route. A state switching time calculation unit 303 calculates, for each route candidate, the time required for switching between forward and backward movements of a vehicle, and the time required to change steering to a predetermined steering angle in a state where the vehicle is stopped. A route selection processing unit 305 selects a specific route, for example, a route with short parking time, from a generated routes based on route passage time.

Abstract: An autonomous driving system of a vehicle includes: an autonomous module configured to, during autonomous driving, control at least one of: steering of the vehicle; braking of the vehicle; and acceleration and deceleration of the vehicle; and a driving control module configured to: enable and disable autonomous driving; determine a future time for beginning a period of autonomous driving; and at least one of: selectively delay the beginning of autonomous driving to after the future time; and cancel the period of autonomous driving.

Abstract: A parking assist system for a vehicle includes a control device configured to control the vehicle to execute an automatic moving process for autonomously moving the vehicle from a current position to a target position. The control device is configured such that, in a case where a parking brake driving condition is satisfied when the control device stops the vehicle during movement to the target position in the automatic moving process and thereafter cancels the automatic moving process without permitting resumption of the movement of the vehicle, the control device switches a shift position of the shift device of the vehicle to a parking position and drives the parking brake device of the vehicle.

Abstract: An artificial intelligence (AI) device installed in a first vehicle includes a sensing unit configured to sense an area in which the first vehicle is moveable at a current position, and a processor configured to receive a request for assignment of control authorization for allowing a first external vehicle to control the first vehicle from the first external vehicle, based on information sensed by the sensing unit, or to make a request to the second external vehicle for assignment of control authorization for allowing the AI device to control a second external vehicle.

Abstract: An update system includes an electronic control device that stores an autonomous driving logic and a server. The server includes: a storage unit storing personal characteristic data based on a user's driving and associated driving result data. In creating a first personal characteristic data associated with a first user ID and a first position, if first driving result data is present, the personal characteristic creating unit creates the first personal characteristic data using the first driving result data. If the first driving result data is not present, the personal characteristic creating unit creates the first personal characteristic data using the driving result data or the personal characteristic data associated with a user ID specified for the first user ID by the similarity specifying unit and the first position. The electronic control device includes a personal characteristic updating unit configured to update the autonomous driving logic using the first personal characteristic.

Abstract: A method for updating a localization of an autonomous vehicle includes receiving perception input data from a sensor of the autonomous vehicle and receiving map data including road lane information in a vicinity of the autonomous vehicle. The method includes processing the perception input data to extract perceived road lane information including a perceived x position, a perceived y position, a perceived z position, a perceived lane type, a perceived lane color, and a perceived lane curvature and processing the map data to extract map road lane information including a map x position, a map y position, a map z position, a map lane type, a map lane color, and a map lane curvature. The method includes calculating a transformation matrix from the perceived road lane information and the map road lane information and updating the map data and a localization of the vehicle based on the transformation matrix.

Abstract: A vehicle control apparatus includes circuitry for controlling a vehicle. The circuitry is configured to search for a stop location where the vehicle is to stop, on a basis of road shoulder region information, generate an evacuation path on a basis of road information to the stop location, and guide the vehicle to the stop location from a first travel lane adjacent to a road shoulder region. The circuitry is further configured to calculate a collision risk of collision with an on-road obstacle. When the collision risk is a predetermined degree or higher, the circuitry is to interrupt the guidance, otherwise the circuitry is to guide the vehicle to enter the stop location and stop the vehicle at the stop location.

Abstract: Embodiments relate to vehicles, apparatuses, methods and computer programs for a vehicle, for a platooning vehicle, and for a network component. The apparatus (10) for a vehicle (100) comprises one or more interfaces (12) configured to communicate in a mobile communication system (400), and a control module (14) configured to control the one or more interfaces (12). The control module (14) is further configured to receive one or more messages from one or more vehicles. The one or more messages comprise information on at least a velocity and a location of a vehicle. The control module (14) is configured to detect whether a potential intruder for a platoon of vehicles is present based on the one or more messages from the one or more vehicles and based on a warning message trigger condition. The control module (14) is configured to generate a warning message in case a potential intruder is detected, and to communicate the warning message to one or more other vehicles.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, with the customer's permission, a vehicle operator in an autonomous or semi-autonomous vehicle may be determined by a sensor disposed within the autonomous or semi-autonomous vehicle or a mobile computing device associated with the vehicle operator. A determination may be made as to whether the vehicle operator is authorized to operate the vehicle based upon the determined identity of the vehicle operator; and if the vehicle operator is not authorized, an alert may be generated and/or the vehicle may be caused to not operate. Alternatively, autonomous operation features may be automatically engaged to automatically drive the autonomous or semi-autonomous vehicle to a safe location when the operator is not authorized. Insurance discounts may be provided based upon the anti-theft functionality.

Abstract: An autonomous driving device includes a first map including a first content and a second content associated with positions respectively, a second map including the first content associated with the position and in which the second content is not a recording target, and a control unit performing the autonomous driving. When the autonomous driving is performed using the first map, the control unit determines information necessary for the autonomous driving using a first method based on the first content and the second content. When the autonomous driving is performed using the second map, the control unit determines the information necessary for the autonomous driving using a method same as the first method based on the first content corresponding to a second position recorded in the second map and information indicating that the second content corresponding to the second position recorded in the second map is not present.

Abstract: A method by a wearable device is described. The method includes receiving geometric information from a controller. The geometric information includes a point cloud and a key frame of the controller. The method also includes receiving first six degree of freedom (6DoF) pose information from the controller. The method further includes synchronizing a coordinate system of the wearable device with a coordinate system of the controller based on the point cloud and the key frame of the controller. The method additionally includes rendering content in an application based on the first 6DoF pose information.

Abstract: A system includes an acquisition unit that acquires an operation amount or a duration count, and a switching unit that switches a driving state. The switching unit switches the driving state to the cooperative driving state when the operation amount is equal to or greater than an intervention threshold and less than a start threshold or the duration count is equal to or greater than a first threshold and less than a second threshold during the autonomous driving state, switches the driving state to the autonomous driving state when the operation amount is less than the intervention threshold or the duration count is less than the first threshold during the cooperative driving state, and switches the driving state to the manual driving state when the operation amount is equal to or greater than the start threshold or the duration count is equal to or greater than the second threshold.

Abstract: A transportation vehicle with a control unit and a method for unparking a transportation vehicle from a parking space, wherein the control unit controls the transportation vehicle at least partly autonomously, wherein the method provides data relating to a current parking situation; determines possible target positionings of the transportation vehicle based on the provided data; determines a probability with which the respective target positioning corresponds to a desired target positioning of a user of the transportation vehicle while taking into account the provided data; orders the target positionings in a ranking according to the probability, and provides the ranking.

Abstract: A navigation system for a host vehicle is provided. The system may comprise at least one processing device programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify at least one vehicle-induced occlusion zone in an environment of the host vehicle; and cause a navigational change for the host vehicle based, at least in part, on a size of a target vehicle that induces the identified occlusion zone.

Abstract: This application relates to techniques for dynamically determining whether to engage an autonomous controller of a vehicle. A computing system may receive a request to engage the autonomous controller (e.g., autonomous mode) of the vehicle. In some examples, the request may be received from a simulation computing system configured to test an updated autonomous controller in a simulation. Based on a determination that conditions associated with engaging autonomy are satisfied, the computing system engages the autonomous controller. Based on a determination that conditions associated with engaging autonomy are not satisfied, the computing system disables the engagement of the autonomous controller such that the vehicle is controlled according to an initial operational mode (e.g., manual mode, semi-autonomous mode, previous version of the autonomous controller, etc.).

Abstract: Aspects of the disclosure relate to controlling a transition between a manual driving mode and an autonomous driving mode of a vehicle. For instance, one or more processors of one or more control computing devices may control the vehicle in the autonomous driving mode. While controlling the vehicle in the autonomous driving mode and decelerating at a given rate, the processors may receive at a user input of the vehicle input requesting a transition from the autonomous driving mode to the manual driving mode. In response to the input, the processors may transition the vehicle to the manual driving mode. After transitioning the vehicle to the manual driving mode, the processors may send deceleration signals to a deceleration actuator thereby causing the vehicle to continue to decelerate at the given rate.

Abstract: Methods and systems are disclosed for correlating synthetic LiDAR data to a real-world domain for use in training an model for use by autonomous vehicle when operating in an environment. To do this, the system will obtain a data set of synthetic LiDAR data, along with images of a real-world environment. The system will transfer the synthetic LiDAR data to a two-dimensional representation, use the two-dimensional representation and the images to train a model that a vehicle can use to operate in a real-world environment.

Abstract: Systems, methods, and non-transitory computer-readable media can determine contextual information associated with an environment including a vehicle and at least one agent for generating a computer simulation based on the environment. One or more behavior constraints for the at least one agent can be determined based on the contextual information. A set of trajectories can be generated based on the one or more behavior constraints. A trajectory can be selected from the set of trajectories based on determining that the trajectory satisfies one or more predetermined criteria. The computer simulation can be generated, wherein the computer simulation includes monitoring driving behavior of the vehicle in response to the vehicle interacting with the at least one agent based on the selected trajectory.

Abstract: Disclosed is a method of providing a scenario-based overlay torque request signal in a steer torque manager (1) during driver-override of an auxiliary steering assistance system (2) function in a road vehicle (3) having an EPAS system (4). The steer torque manager (1) has a wheel angle controller (1b) for providing an assistance torque request related signal, and a driver-in-the-loop functionality (1a) for determining driver-override and providing a driver-override related signal.

Abstract: [Problem] To provide an automatic driving robot control device and control method that enable a vehicle to be operated smoothly while also being caused to conform to a command vehicle speed with high accuracy.

Abstract: A method and an apparatus for planning a speed of an autonomous vehicle, and a storage medium are provided. The method includes: generating a plurality of speed trajectories to be selected for the autonomous vehicle before the autonomous vehicle changes a lane; obtaining predicted speeds and predicted positions of an obstacle at the plurality of time points; calculating a cost function value of each of the speed trajectories to be selected, according to the plurality of speed trajectories to be selected, the predicted speeds and the predicted positions; and selecting a speed trajectory to be selected with a minimum cost function value as a planning speed trajectory of the autonomous vehicle. A speed of the autonomous vehicle can be adjusted before the autonomous vehicle changes a lane, thereby creating an opportunity and a safe distance for the lane change, and improving a success rate of the lane change.

Abstract: A display control unit displays a background of a touch panel in a first color and does not display a button for starting autonomous driving on the touch panel when an autonomous driving vehicle is not permitted to travel in autonomous driving from a management center and displays the background of the touch panel in a second color different from the first color and displays an autonomous driving start button for starting the autonomous driving on the touch panel when the autonomous driving vehicle is permitted to travel in autonomous driving from the management center.

Abstract: An embodiment vehicle includes a camera, a speaker, and a controller electrically connected to the camera and the speaker, wherein the controller is configured to acquire a first external image outside the vehicle from the camera, input the first external image to a pre-trained first neural network and extract a first feature corresponding to the first external image, and control the speaker to output a first sound sample among a plurality of sound samples, based on a comparison of the first feature and pre-stored features corresponding to the plurality of sound samples.

Abstract: In particular embodiments, a computing system may determine a measured driving characteristic of a driving control system based on observations of vehicles driven by the driving control system. The system may determine a difference between the measured driving characteristic and a target driving characteristic, which is based on objectivations of one or more manually controlled vehicles. The system may determine an evaluation objective for the driving control system. The system may determine a weight function for the evaluation objective. The system may determine a score for the driving control system with respect to the evaluation objective by weighting the difference between the measured driving characteristic and the target driving characteristic using the weight function. The system may apply, based on the score, an adjustment to the driving control system to reduce a difference between a subsequently measured driving characteristic of the driving control system and the target driving characteristic.

Abstract: This description provides an autonomous or semi-autonomous excavation vehicle that is capable determining a route between a start point and an end point in a site and navigating over the route. The sensors collect any or more of spatial, imaging, measurement, and location data to detect an obstacle between two locations within the site. Based on the collected data and identified obstacles, the excavation vehicle generates unobstructed routes circumventing the obstacles, obstructed routes traveling through the obstacles, and instructions for removing certain modifiable obstacles. The excavation vehicle determines and selects the shortest route of the unobstructed and obstructed route and navigates over the selected path to move within the site.

Abstract: A drive mode switch control device acquires operation information. The drive mode switch control device switches a drive state among at least an autonomous drive state, a manual drive state, and a coordination drive state. The operation detection unit detects a first operation and a second operation based on the operation information when the drive state is not in the manual drive state. The second operation is the drive operation different from the first operation and input after the input of the first operation. The drive mode switch control device switches the drive state from the autonomous drive state to the coordination drive state based on a detection determination of the first operation. The drive mode switch control device switches the drive state from the coordination drive state to the manual drive state based on a detection determination of the first operation.