Abstract: A start control device for a hybrid vehicle includes a battery, first and second rotary electric machines, an engine, a first determination unit configured to determine whether the battery is in a low output state, a cranking control unit configured to perform a cracking of the engine, and a second determination unit configured to perform a cranking completion determination. In a case where a maximum output of the battery is in the low output state, the cranking control unit causes the first rotary electric machine to run at a low output target rotation speed, and the second determination unit determines that the cranking is completed when a condition that an actual rotation speed of the first rotary electric machine continues to be within a target range for a predetermined time is satisfied.

Abstract: The various embodiments described herein generally relate to an autonomous material transport vehicle, and systems and methods for operating an autonomous material transport vehicle. The autonomous material transport vehicle comprises: a sensing system operable to monitor an environment of the vehicle; a drive system for operating the vehicle; a processor operable to: receive a location of a load; initiate the drive system to navigate the vehicle to the location; following initiation of the drive system, operate the sensing system to monitor for one or more objects within a detection range; and in response to the sensing system detecting the one or more objects within the detection range, determine whether the load is within the detection range; and when the load is within the detection range, operate the drive system to position the vehicle for transporting the load, otherwise, determine a collision avoidance operation to avoid the one or more objects.

Abstract: Embodiments may relate to a vehicle comprising: a sensor to identify, based on an audio or visual condition, the occurrence of a condition related to a passenger of the vehicle. The vehicle may further include a processor coupled with the sensor. The processor may be configured to identify, in a user profile of the first passenger of the vehicle, a pre-identified action. The processor may further be configured to perform, or facilitate the performance of, the pre-identified action by the vehicle based on the occurrence of the audio or visual condition. Other embodiments may be described or claimed.

Abstract: Vehicles may have autonomous capabilities that permit the vehicle to navigate according to varying levels of participation by a human operator. A human operator may be associated with a driving capability profile and the environment surrounding a vehicle may be associated with an environmental risk profile. A vehicle, or another party in communication with a vehicle, may determine whether, based on the human operator's driving capability profile and the environmental risk profile, it is likely that the vehicle will be navigated more safely if there is a change to the vehicle's autonomous capabilities and a corresponding change to the human operator's driving responsibilities. If it is determined that a change in autonomous vehicle capability is likely to increase safe navigation of the vehicle, an insurer may offer an insurance premium cost reduction if the human operator agrees to the proposed change in autonomous capabilities.

Abstract: A vacuum cleaner for performing autonomous driving may include: a main body; a driving unit; a suctioning unit; a plurality of sensors for sensing obstacles present in each direction; and a control unit for controlling the driving unit to move the main body on the basis of a preset driving pattern. The control unit uses sensors provided at the front side of the main body and a first side of the both sides of the main body so as to detect whether entry into a corner area among cleaning areas is made while driving along the preset driving pattern, and controls the driving unit such that the first side of the main body comes into contact with a first wall forming the corner area at least one time when the main body enters the corner area.

Abstract: An information processing method to be executed by a computer includes: obtaining a driving skill of a person who rides an autonomous vehicle, which represents at least one of whether the person can drive a manually-drivable autonomous vehicle or a level at which the person can drive; obtaining specifications of autonomous vehicles about autonomous driving; obtaining a route for transporting the person; determining deviation risks, each of which includes at least one of a possibility of deviation of an autonomous driving system including a corresponding one of the autonomous vehicles from an operational design domain or a degree of the deviation, based on the specifications and the route; selecting an autonomous vehicle assigned to transportation of the person from the autonomous vehicles according to each of the deviation risks and the driving skill; and sending a notification of the selected autonomous vehicle.

Abstract: Systems, methods, and autonomous vehicles for automated lane conflict estimation may obtain map data associated with a map of a geographic location including a roadway, determine, based on the map data, a relative lane geometry between a first lane segment and a second lane segment of a pair of overlapping lane segments; process, with a machine learning model, the relative lane geometry and a type of a traffic signal or sign associated with the pair of overlapping lane segments to generate a prediction of whether the first lane segment yields to the second lane segment for a given state of the traffic signal or sign; and use the prediction to at least one of generate a map including the lane segment associated with the prediction, facilitate at least one autonomous driving operation of an autonomous vehicle, or any combination thereof.

Abstract: A method for operating a motor vehicle in the event of an unavoidable collision with a collision object, in particular another vehicle. Environment data relating to the collision object are determined by an environment sensor device including at least one environment sensor and are evaluated to determine at least one driving intervention information for reducing the consequences of a collision. The motor vehicle is automatically guided in accordance with the driving intervention information, and the evaluation of the environment data is carried out together with structural information of the own motor vehicle describing the vehicle structure, in particular including elements absorbing collision energy of the motor vehicle, in such a way that a changed collision point maximizing the deformation energy absorbed by the vehicle structure and to be produced by the driving intervention information is determined when the driving intervention information is determined.

Abstract: Systems and methods for trajectory prediction are provided. A method can include obtaining LIDAR data, radar data, and map data; inputting the LIDAR data, the radar data, and the map data into a network model; transforming, by the network model, the radar data into a coordinate frame associated with a most recent radar sweep in the radar data; generating, by the network model, one or more features for each of the LIDAR data, the transformed radar data, and the map data; combining, by the network model, the one or more generated features to generate fused feature data; generating, by the network model, prediction data based at least in part on the fused feature data; and receiving, as an output of the network model, the prediction data. The prediction data can include a respective predicted trajectory for a future time period for one or more detected objects.

Abstract: Systems and methods for modifying operation of an autonomous vehicle in an emergency situation are disclosed. According to aspects, a computing device associated with the autonomous vehicle detects, based on sensor(s), an emergency event associated with the autonomous vehicle. In response to detecting the emergency event, the computing device determines location(s) of emergency vehicle(s) and determines an assistance location for the autonomous vehicle. The computing device determines which of the emergency vehicle(s) is a nearest emergency vehicle that is nearest to the assistance location, and transmits the assistance location to the nearest emergency vehicle. The computing device then causes the autonomous vehicle to travel to the assistance location.

Abstract: An autonomous mobile device (AMD) moves around a physical space while performing tasks. The AMD may have sensors with fields of view (FOVs) that are forward-facing. As the AMD moves forward, a safe region is determined based on data from those forward-facing sensors. The safe region describes a geographical area clear of obstacles during recent travel. Before moving outside of the current FOV, the AMD determines whether a move outside of the current FOV keeps the AMD within the safe region. For example, if a path that is outside the current FOV would result in the AMD moving outside the safe region, the AMD modifies the path until poses associated with the path result in the AMD staying within the safe region. The resulting safe path may then be used by the AMD to safely move outside the current FOV.

Abstract: Systems, methods, and computer readable medium are provided for determining a wall loss measurement associated with corrosion and/or erosion present within an insulated pipe. A inspection image is acquired for a pipe wall of an insulated pipe at a first location and used to determine an inspection thickness of the pipe wall at the first location. An amount of wall loss measurement can be determined based on a difference of a nominal thickness for the pipe wall at the first location and the determined inspection thickness. The wall loss measurement can characterize an amount of wall material lost due to corrosion and/or erosion present in the pipe wall at the first location. The wall loss measurement can be output for further processing and/or display.

Abstract: An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Abstract: A control method, for the semi-automatic transfer of a driven utility vehicle into a sensor-identifiable target position, includes sensing a relative position of the utility vehicle in relation to the target position and deriving, from the relative position, an automatic, rules-based lateral control of the utility vehicle configured to, together with a longitudinal control, transfer the utility vehicle into the target position. The method further includes detecting, with the aid of a remote control transmitter of the utility vehicle, the presence of an activation signal generated by an operator located outside of the utility vehicle, initiating, in response to the detection of the presence of the activation signal, the transfer of the utility vehicle according to the lateral control and the longitudinal control, and detecting an absence of the activation signal and interrupting the transfer to bring the utility vehicle to a standstill.

Abstract: The present disclosure provides a neural network-based method for calibration and localization of an indoor inspection robot. The method includes the following steps: presetting positions for N label signal sources capable of transmitting radio frequency (RF) signals; computing an actual path of the robot according to numbers of signal labels received at different moments; computing positional information moved by the robot at a tth moment, and computing a predicted path at the tth moment according to the positional information; establishing an odometry error model with the neural network and training the odometry error model; and inputting the predicted path at the tth moment to a well-trained odometry error model to obtain an optimized predicted path. The present disclosure maximizes the localization accuracy for the indoor robot by minimizing the error of the odometer with the odometry calibration method.

Abstract: The disclosure generally pertains to battery charging management of battery electric vehicles (BEVs). In an example method, a processor generates an operational profile for a first BEV among a number of BEVs. The profile may be based on a mileage accumulation pattern, a parking pattern, and/or a battery charging pattern, detected over an information collection period. The mileage accumulation pattern may be based on the use of the first BEV for commuting from a residence to a workplace. The processor determines an availability of a battery charging outlet in a section of a garage of the residence, and based on the operational profile of the first BEV, identifies a period of time for charging a battery of the first BEV in the garage. The processor then issues a directive to park the first BEV in the section of the garage over the identified period of time for charging the battery.

Abstract: A charging station is disclosed. The disclosed charging station comprises: a charging member configured to come into contact with a charging terminal of a robot vacuum cleaner to provide power to the charging terminal; a first light emitting member for emitting an infrared signal; and a reflecting member disposed to face the first light emitting member and reflect an infrared signal emitted from the first light emitting member, toward the front and sides of the charging station.

Abstract: A server device 2 stores a distribution map DB 21 including autonomous driving regulatory information Ir for regulating autonomous driving of a vehicle in a predetermined section, and sends map data D1 including the autonomous driving regulatory information Ir to a driving assistance device 1. Then, the driving assistance device 1 receives the map data D1 including the autonomous driving regulatory information Ir and controls the autonomous driving of the vehicle based on the received autonomous driving regulatory information Ir.

Abstract: Systems and methods for providing autonomous vehicle assistance are disclosed. In one embodiment, a method is disclosed comprising detecting a service condition in response to a fault occurring at an autonomous vehicle at a first location; coordinating service with a nearby service provider, the service provider providing a time window and a second location; predicting that the autonomous vehicle will be free to fulfill the service; driving the autonomous vehicle to the second location of the service provider during the time window; and returning the autonomous vehicle to the first location after the service is completed.

Abstract: A system that may include a first route circuit that may be configured to be coupled with a first route section and may be configured to generate a first location coded signal that is unique to the first route section responsive to a vehicle being located on or within the first route section. A second route circuit may be configured to be coupled with a second route section and configured to generate a second location coded signal that is unique to the second route section and that is different from the first location coded signal, the second route circuit configured to generate the second location coded signal responsive to the vehicle being located on or within the second route section. A controller may be configured to receive the first location coded signal and the second location coded signal and determine a location of the vehicle based on the first location coded signal or the second location coded signal.

Abstract: A first driving solution for a vehicle along a portion of a route is determined based on an agent detected in the vehicle's environment following a first trajectory of a plurality of possible trajectories. A switching time is determined for the vehicle to deviate from the first driving solution for a situation in which the agent is following a second trajectory of the plurality of possible trajectories. The first driving solution is revised such that the vehicle will be able to switch from the revised first driving solution to another driving solution at the switching time in case if the detected agent is following the second trajectory.

Abstract: A vehicle speed/headway control function and a lane-keeping function are provided as driving assist functions to assist in a driving operation by a driver. A mode-switching controller is provided for switching between the modes. In the lane-keeping assist mode, it is assessed whether or not a traveling condition has been met that an actual vehicle speed of the host vehicle exceeds a speed limit of a roadway on which the host vehicle is traveling during lane-keeping travel in which “hands-off mode,” which allows the driver to remove their hands from the steering wheel, has been selected. The mode is switched from “hands-off mode” to “hands-on mode,” which has as a condition that the driver has their hands on the steering wheel, upon assessing that the traveling condition that the actual vehicle speed exceeds the speed limit has been met.

Abstract: Systems, methods, and other embodiments described herein relate to adaptively selecting a controller for generating vehicle controls. In one embodiment, a method includes, in response to acquiring sensor data about a surrounding environment of the vehicle, determining a driving context of the vehicle in relation to aspects of a roadway on which the vehicle is traveling. The method includes selecting a controller for generating control inputs to the vehicle according to the driving context by selecting between a proportional, integral, derivative (PID) controller and a machine learning (ML) controller. The method includes controlling the vehicle using the controller.

Abstract: An interactive system (1) for interacting with a user is disclosed. The interactive system (1) includes at least one interface (3), a measuring device (5), and a processing unit (7) comprising an interpretation module for receiving a physiological parameter obtained by the measuring device (5) and for defining, based on the physiological parameter, a datum representative of the physiological state of the user (U). The processing unit (7) comprises a data communication module for communicating data with a server (11) storing a library of applications, a data processing module for selecting an application on the basis of the datum representative of the physiological state, an information module for notifying the user (U) of the selected application, and detecting a validation action from the user (U) validating the notified application, and a download module for downloading the validated application.

Abstract: A vehicle system includes: a map processing unit that creates local map data based on high accuracy map data and a position of an own vehicle; and an autonomous driving control unit that creates a travel plan for autonomous traveling of the own vehicle based on the local map data and controls traveling of the own vehicle according to the travel plan. The map processing unit creates multiple pieces of transmission data by dividing the local map data so as to correspond to regions on a map and transmits the multiple pieces of transmission data to the autonomous driving control unit. The map processing unit changes a shape and a size of the region on the map corresponding to each piece of transmission data based on selection information which decides a travel mode.

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 vehicle control method includes: detecting, on a planned travel route of a host vehicle, a merging section in which a travel lane in which the host vehicle is traveling merges with another lane; determining whether or not to execute merging assistance control for assisting the host vehicle to change lanes into the other lane in the merging section; and when the merging assistance control is determined not to be executed in the merging section, controlling the speed of the host vehicle to be a predetermined speed or less before the host vehicle passes through a starting point of the merging section.

Abstract: As a farming machine travels through a field of plants, the farming machine operates in a normal operational state to perform one or more farming operations. The farming machine detects an operational failure of a component of the farming machine using measurements obtained from one or more sensors coupled to and monitoring the farming machine. The operational failure of the component impacts performance of a first farming operation of the farming operations. The farming machine configures the farming machine to operate in a remedial operational state. In the remedial operational state, the farming machine diagnoses the operational failure of the component using the obtained measurements. In the remedial operational state, the farming machine selects a solution operation to address the operational failure of the component based on the diagnosis. The farming machine performs the determined solution operation.

Abstract: A vehicle control apparatus includes an automatic-driving processor and an engine processor. The automatic-driving processor is configured to perform an automatic-driving control to stop a vehicle in accordance with detection of an abnormal state of a driver who drives the vehicle while the vehicle is traveling. When the vehicle is in a standby state after stopping of the vehicle by the automatic-driving control, the engine processor is configured to perform an engine driving control to reduce how frequently an engine of the vehicle is started, compared with when the vehicle is in a normal traveling state. The standby state is a state in which an operation control of an air conditioner of the vehicle is allowed.

Abstract: The technology relates to assisting large self-driving vehicles, such as cargo vehicles, as they maneuver towards and/or park at a destination facility. This may include a given vehicle transitioning between different autonomous driving modes. Such a vehicles may be permitted to drive in a fully autonomous mode on certain roadways for the majority of a trip, but may need to change to a partially autonomous mode on other roadways or when entering or leaving a destination facility such as a warehouse, depot or service center. Large vehicles such as cargo truck may have limited room to maneuver in and park at the destination, which may also prevent operation in a fully autonomous mode. Here, information from the destination facility and/or a remote assistance service can be employed to aid in real-time semi-autonomous maneuvering.

Abstract: A virtual railroad of vehicles is disclosed. In one aspect of the disclosure, a system includes one or more passenger vehicles of a peloton, and a first engine vehicle of the peloton. The first engine vehicle communicatively connected to the one or more passenger vehicles, wherein the first engine vehicle comprises: a processor communicatively connected to a memory and is configured to receive status information of the one or more passenger vehicles, determine, based on the received status information, a set of current values for a set of vehicle attributes for each of the one or more passenger vehicles, and adjust, based on the set of current values for the set of vehicle attributes, a position of a corresponding passenger vehicle of the one or more passenger vehicles.

Abstract: An automatic parking system configured to cause an autonomous vehicle to travel autonomously from a parking space to a pickup area based on a parking space departure time determined such that the autonomous vehicle arrives the pickup area at a scheduled pickup time that is predetermined. The automatic parking system includes an on-control time setting unit configured to set an on-control time at which a state of the autonomous vehicle is controlled to be a power-on state based on the parking space departure time, and a power-on control unit configured to control the state of the autonomous vehicle to be the power-on state based on the on-control time that is set. The on-control time setting unit is configured to set the on-control time such that the power-on state is established prior to the parking space departure time.

Abstract: Real-time decision-making for a vehicle using belief state determination is described. Operational environment data is received while the vehicle is traversing a vehicle transportation network, where the data includes data associated with an external object. An operational environment monitor establishes an observation that relates the object to a distinct vehicle operation scenario. A belief state model of the monitor computes a belief state for the observation directly from the operational environment data. The monitor provides the computed belief state to a decision component implementing a policy that maps a respective belief state for the object within the distinct vehicle operation scenario to a respective candidate vehicle control action. A candidate vehicle control action is received from the policy of the decision component, and a vehicle control action is selected for traversing the vehicle transportation from any available candidate vehicle control actions.

Abstract: Embodiments of the present invention relate to the technical field of unmanned aerial vehicles (UAV), and specifically discloses an automatic return method, device and UAV. By means of the foregoing technical solutions, the embodiments of the present invention can estimate a minimum power consumption required for the UAV to return from the current position to the return point in a more accurate way, so as to avoid forced landing of the UAV due to an excessively low battery level during a flight or a return.

Abstract: A vehicle adjustment system includes one or more processors configured to receive data from one or more sensors coupled to a vehicle that is in a stationary position. The one or more processors are also configured to analyze the data to determine whether an object is within a buffer zone surrounding the vehicle while the vehicle is in the stationary position. In response to determining that the object is within the buffer zone while the vehicle is in the stationary position, the one or more processors are configured to provide control signals to one or more driving components of the vehicle to reposition the vehicle to an alternate position.

Abstract: A method and apparatus is provided for controlling the operation of an autonomous vehicle. According to one aspect, the autonomous vehicle may track the trajectories of other vehicles on a road. Based on the other vehicle's trajectories, the autonomous vehicle may generate a pool of combined trajectories. Subsequently, the autonomous vehicle may select one of the combined trajectories as a representative trajectory. The representative trajectory may be used to change at least one of the speed or direction of the autonomous vehicle.

Abstract: The invention relates to a method for creating a semantic representation of the environment of a vehicle, having the following steps: acquiring (S1) sensor measuring data by means of at least one first (2a) and/or second environment detection sensor (2b) of the vehicle, detecting (S2) objects and free spaces in the environment of the vehicle, creating (S3) a grid map having occupied and free grid cells based on the detected objects and free spaces; determining (S4) height information by means of the at least one first (2a) and/or second environment detection sensor (2b); adding (S5) the height information to each grid cell; allocating (S6) semantic information to the grid cells based on the height information.

Abstract: An automatic driving system includes a control device that controls automatic driving of a vehicle, and a storage device that contains external environment information indicating an external environment of the vehicle. A driving transition zone is a zone in which a driver of the vehicle takes over at least a part of driving of the vehicle, from the control device. A termination target velocity is a target velocity of the vehicle at an end point of the driving transition zone. The control device variably sets the termination target velocity, depending on the external environment at the end point or the external environment surrounding the end point. Then, the control device controls the velocity of the vehicle in the driving transition zone, such that the velocity of the vehicle at the end point is the termination target velocity.

Abstract: The present disclosure discloses a multifunctional cleaning machine. The multifunctional cleaning machine includes a housing, a pipe, a nozzle, a plurality of wheel assemblies and a locking means. The pipe connected to the housing, the pipe including a water inlet and a water outlet, the water inlet being located on an upper side of the housing, the water outlet being located on a lower side of the housing, and the water inlet being configured for connecting to a high pressure water source. The nozzle connected to the water outlet. The wheel assemblies rotatably connected to the housing by the connecting assembly. The locking means connected to the housing and configured for locking the wheel assembly.

Abstract: A vehicle system, including: a steering system; and a longitudinal-force application system including longitudinal-force application actuators configured to apply longitudinal forces respectively to one or more left-side wheels and one or more right-side wheels and a longitudinal-force controller configured to control the longitudinal-force application actuators to control the longitudinal forces applied respectively to the one or more left-side wheels and the one or more right-side wheels, and an onboard power source device including a main power source and a secondary power source. When the main power source fails to supply electric power to the longitudinal-force application system and the steering system, the longitudinal-force controller controls the longitudinal-force application actuators to control a difference between the longitudinal force applied to the one or more left-side wheels and the longitudinal force applied to the one or more right-side wheels, thereby turning the vehicle.

Abstract: Aspects of the disclosure relate to controlling autonomous vehicles to optimize traffic characteristics. A computing platform may receive vehicle guidance data from autonomous vehicle control systems of vehicles. Subsequently, the computing platform may identify a number of the vehicles currently operating in an autonomous mode based on the vehicle guidance data. Thereafter, the computing platform may identify a target number of the vehicles to be operated in an autonomous mode in order to optimize traffic characteristics. Then, the computing platform may generate messages directing selected vehicles to switch into autonomous mode in order to achieve the target number. Subsequently, the computing platform may send the messages directing the selected vehicles to switch into autonomous mode in order to receive incentives. Thereafter, the computing platform may award the incentives to the selected vehicles that switch into the autonomous mode as directed by the messages.

Abstract: This application relates to techniques for determining whether to engage an autonomous controller of a vehicle based on previously recorded data. A computing system may receive, from a vehicle computing system, data representative of a vehicle being operated in an environment, such as by an autonomous controller. The computing system may generate a simulation associated with the vehicle operation and configured to test an updated autonomous controller. The computing system may determine one or more first time periods associated with the vehicle operations that satisfy one or more conditions associated with engaging an autonomous controller and one or more second time periods associated with the vehicle operations that fail to satisfy the one or more conditions. The computing system may enable an engagement of the autonomous controller during the one or more first time periods and disable the engagement during the one or more second time periods.

Abstract: Velocity adjustments based on roadway scene comprehension may include controlling an ego vehicle traveling in a first lane, wherein the first lane comprises a lane of travel for the ego vehicle of a multilane roadway including at least the first lane and a second lane; capturing object ranges by the ego vehicle using at least a first sensor corresponding to a first sensor type; identifying a first vehicle operating in the second lane from the first sensor; determining a first velocity of the first vehicle; generating a first lane flow rate for the second lane from one or more captured object velocities, wherein the lane flow rate of the second lane is based on at least the first velocity of the first vehicle and a traffic density estimation; determining whether to modify an ego vehicle velocity based on the first lane flow rate; and in response to determining whether to modify the ego vehicle velocity, generating instructions for the ego vehicle's velocity.

Abstract: An automatic parking system includes an infrastructure sensor that is able to detect a state of a parking lot. A blind spot area that does not allow the state of the parking lot to be detected by the infrastructure sensor is identified in the parking lot, and the state of the parking including the blind spot area, the state of the parking lot being detected by an on-board sensor of a vehicle in the parking lot, is acquired. Based on the state of the parking lot detected by the infrastructure sensor and the state of the parking lot that includes the blind spot area and that is detected by the on-board sensor of the vehicle in the parking lot, a travel route for the vehicle traveling in the parking lot is generated.

Abstract: A method for simulation of an autonomous vehicle includes preparing a setting of a parameter and an initial value configured to determine a driving condition of the autonomous vehicle and a driving condition of an event to be performed by a surrounding vehicle to implement a simulation environment of the autonomous vehicle. The method further includes performing a normal driving in which the surrounding vehicle travels at a speed and a position that match a predetermined condition set in the parameter to perform the event given, and performing an event driving in which the surrounding vehicle performs the event given based on a setting value of the parameter.

Abstract: Systems and methods are provided for managing private digital authentication information, known as secrets, for autonomous vehicles. In particular, systems and methods are provided for automating the acquisition of secrets by autonomous vehicles upon start-up, such that secrets are not stored on autonomous vehicles that are powered down. A secrets manager is installed on each autonomous vehicle that can request sets of secrets at start-up and provide the secrets to various modules in the vehicle. Secrets can be updated centrally and autonomous vehicles can easily access updated secrets.

Abstract: A control device for a vehicle is configured to request that a driver grip a steering wheel at the time of a predetermined driving scene, judge whether a steering wheel grip status is a one-handed grip status or a two-handed grip status, and judge based on the steering wheel grip status whether the status is a grip completion status where the steering wheel has finished being gripped. The control device is further configured to change whether to judge the status is a grip completion status if at least a one-handed grip status or to judge whether the status is a grip completion status only if a two-handed grip status in accordance with the driving scene.

Abstract: A system and method for utilizing multiple driver stations in a track vehicle is described. A primary driver station can utilize controls with hybrid drive by wire (DbW) functionality (i.e. hydro-mechanical and electric control). A secondary driver station and a tertiary driver station can utilize controls with DbW (i.e. electronic) control systems. The secondary and tertiary driver stations can be adapted for autonomous driving. The invention also includes a method of transfer between driver stations with safeguards for safety and reliability.

Abstract: A method for interactions during encounters between a mobile robot and an actor, a mobile robot configured for execution of delivery tasks in an outdoor environment, and a use of the mobile robot. The method comprises the mobile robot traveling on a pedestrian pathway; detecting an actor by the mobile robot via a sensor system; identifying a situation associated with the detected actor; in response to the identified situation, determining an action to execute by the mobile robot, and executing the determined action by the mobile robot. The mobile robot comprises a navigation component configured for at least partially autonomous navigation in an outdoor environment; a sensor system configured for collecting sensor data during an encounter between the mobile robot and an actor; a processing component configured to process the sensor data and output actions for the mobile robot to perform; and an output component configured for executing actions determined by the processing component.

Abstract: Whether a vehicle is parked inside parking lines in a parking lot is detected. When the vehicle is detected not parked inside the parking lines, either the vehicle or the parking lines are moved in such a manner that the vehicle is parked inside the parking lines.