Abstract: A method for controlling a driving condition component of an autonomous vehicle is presented. The method includes determining whether current conditions would limit a driver's visibility. The method also includes predicting whether the driver will enable a manual mode during the current conditions. The method further includes controlling the driving condition component to mitigate the current conditions prior to the driver enabling the manual mode.

Abstract: An autonomous driving device is configured to switch a driving mode, and includes a destination setting type autonomous driving mode in which a vehicle is made to travel to a destination and a following road autonomous driving mode in which, when a destination is not set, the vehicle is made to travel along a road. The autonomous driving device includes a display unit and an electronic control unit. The electronic control unit is configured to, when the display unit is made to display a traveling route along a following road traveling route, make the display unit display a traveling route from a current position of the vehicle to a nearest branch road in front in a moving direction along the following road traveling route and a moving direction on the nearest branch road along the following road traveling route.

Abstract: A method for selecting an autonomous mobility-as-a-service (MAAS) vehicle is presented. The method includes transmitting, to a customer, location information of an autonomous MAAS vehicle within the customer's vicinity. The method also includes transmitting, to the customer, a compartment climate value corresponding to the autonomous MAAS vehicle. The method further includes selecting the autonomous MAAS vehicle based on the compartment climate value, such that the selected autonomous MAAS vehicle navigates to a location of the customer.

Abstract: In one embodiment, a method for collecting lane data is disclosed. The method includes collecting lane data, for a lane of a plurality of lanes of a road, from one or more sensors of a vehicle traveling in the lane. The method includes receiving an identifier of a lane of the plurality of lanes. The identified lane is a lane-of-interest and is different from the lane that the vehicle is traveling in. The method includes determining that the vehicle is not occupied. The method includes causing, in response to determining that the vehicle is not occupied, the vehicle to travel in the lane-of-interest. The method includes collecting lane data, for the lane-of-interest from the one or more sensors.

Abstract: In one embodiment, a method for collecting lane data is disclosed. The method includes collecting lane data for a first lane of a plurality of lanes of a road from one or more sensors of a vehicle traveling in the first lane. The method includes receiving an identifier of a lane-of-interest from the plurality of lanes. The method includes determining a probability that the vehicle will receive a ride request while traveling in the first lane. The method includes determining that the probability satisfies a threshold. The method includes, in response to determining that the probability satisfies the threshold, causing the vehicle to travel in the lane-of-interest. The method includes collecting lane data for the lane-of-interest from the one or more sensors.

Abstract: A method for route planning for an autonomous vehicle includes determining whether a route to a destination includes a stall factor and determining whether the autonomous vehicle will be occupied during the route. The method also includes determining an alternate route based on the determined stall factor when the autonomous vehicle will be unoccupied. The method still further includes controlling the autonomous vehicle to drive on the alternate route when the alternate route does not include a stall factor.

Abstract: A method for adjusting a seat in a vehicle is presented. The method includes receiving a user input from a passenger to adjust the seat from a default position to a passenger adjusted position. The method also includes predicting, in response to the passenger exiting the vehicle, a likelihood of the passenger returning to the vehicle. The method still further includes maintaining the passenger adjusted position when the likelihood of the passenger returning to the vehicle is greater than a threshold.

Abstract: An autonomous driving device for a vehicle includes: an actuator; and an electronic control unit configured to detect presence or absence of a driver, generate a first travel plan for causing the vehicle to travel autonomously, and generate a second travel plan by adding, to the first travel plan, a restriction including at least one of a lane change restriction and a vehicle speed restriction. The electronic control unit is configured to perform manned autonomous driving control for causing the vehicle to travel autonomously, by using the actuator, with the driver in the vehicle according to the first travel plan when the presence of the driver is detected, and perform unmanned autonomous driving control for causing the vehicle to travel autonomously, by using the actuator, with the driver not in the vehicle according to the second travel plan when the absence of the driver is detected.

Abstract: A remote autonomous driving vehicle transmits sensor information detected by a sensor to a remote instruction apparatus, and travels based on a remote instruction from a remote commander. The remote autonomous driving vehicle includes a sensor type determination unit configured to determine a type of the sensor that transmits the sensor information to the remote instruction apparatus based on an external environment and map information; and a sensor information transmission unit configured to transmit the sensor information detected by the sensor of which the type is determined by the sensor type determination unit to the remote instruction apparatus.

Abstract: A vehicle remote instruction system includes a remote instruction point situation recognition unit that recognizes a remote instruction point situation on a target route based on the target route, position information, and map information, a recommended time acquisition unit that acquires a recommended time based on the remote instruction point situation and a type of a remote instruction, a remote instruction sending unit that sends the remote instruction to an autonomous driving vehicle, and a predicted time calculation unit that calculates a predicted time. The remote instruction sending unit sends a delay instruction to set a reflection time closer to the recommended time when the predicted time is earlier than the recommended time, and sends a preparation instruction to cause the autonomous driving vehicle to behave in response to the type of the remote instruction at an earlier time when the predicted time is later than the recommended time.

Abstract: A vehicle remote instruction system 100 transmits a remote instruction request from an autonomous driving vehicle 2 to a remote instruction apparatus 1, and controls travel of the autonomous driving vehicle 2 based on a remote instruction transmitted from the remote instruction apparatus 1 in response to the remote instruction request. The vehicle remote instruction system 100 includes a delay determination unit 39 configured to determine whether or not a communication delay occurs between the remote instruction apparatus 1 and the autonomous driving vehicle 2, and a rejection unit 40 configured to reject the remote instruction transmitted in response to the remote instruction request if it is determined by the delay determination unit 39 that the communication delay occurs.

Abstract: A drive assist device includes a display that displays an image around a vehicle imaged by an imaging device installed on the vehicle, a setting unit that sets a target designated by a user on the image as a recognition target, a detection unit that detects a state change of the recognition target on the image in a case where the recognition target is set, and a notification control unit that controls a notification device to notify the user of the detection result in a case where the state change of the set recognition target is detected.

Abstract: A vehicle remote instruction training device that trains a remote commander who issues a remote instruction to an actual autonomous vehicle includes: a commander interface including an information output unit that shows a situation of the actual autonomous vehicle to the remote commander and an instruction input unit for the remote commander to input the remote instruction to the actual autonomous vehicle; a virtual situation display unit that shows a virtual situation of a virtual vehicle with time variation to a remote commander who is a trainee through the information output unit; a remote instruction input recognition unit that recognizes an input of the remote instruction input into the instruction input unit; and an evaluation unit that evaluates the remote commander based on timing at which they issue the remote instruction with respect to the virtual situation of the virtual vehicle or on a content of the remote instruction.

Abstract: A vehicle remote instruction system includes a remote instruction point situation recognition unit configured to recognize a remote instruction point situation on a target route preset for an autonomous vehicle, based on the target route, location information of the autonomous vehicle, and map information; a time prediction unit configured to predict monitoring start and end times of a remote commander for the remote instruction point situation on the target route, from a preset vehicle speed or a vehicle speed plan of the autonomous vehicle, based on the target route, the location information, the map information, and the remote instruction point situation; and a monitoring time allocation unit configured to allocate a monitoring time to a plurality of remote commanders based on the monitoring start and end times of the remote instruction point situation in a plurality of autonomous vehicles.

Abstract: Systems and methods are provided for generating trajectories for a vehicle user interface showing a driver's perspective view. Methods include generating an ego-vehicle predicted trajectory for an ego-vehicle; and generating at least one road agent predicted trajectory for a road agent that is external to the ego-vehicle. After the predicted trajectories are generated, the method continues by determining that at least one predicted trajectory overlaps either an object or another predicted trajectory, when displayed on the user interface showing a driver's perspective view. The method includes modifying the at least one road agent predicted trajectory to remove the overlap. The method then proceeds with updating a display of the user interface to include any modified road agent predicted trajectory. Systems include a trajectory-prediction module to execute the methods.

Abstract: Systems and methods are provided for generating trajectories for a vehicle user interface showing a driver's perspective view. Methods include generating an ego-vehicle predicted trajectory for an ego-vehicle; and generating at least one road agent predicted trajectory for a road agent that is external to the ego-vehicle. After the predicted trajectories are generated, the method continues by determining that at least two predicted trajectories overlap when displayed on the user interface showing a driver's perspective view, when displayed on the user interface showing a driver's perspective view. The method includes modifying the at least one road agent predicted trajectory to remove the overlap. The method then proceeds with updating a display of the user interface to include any modified road agent predicted trajectory. Systems include a trajectory-prediction module to execute the methods.

Abstract: Systems and methods are provided for generating trajectories for a vehicle user interface showing a driver's perspective view. Methods include generating an ego-vehicle predicted trajectory for an ego-vehicle; and generating at least one road agent predicted trajectory for a road agent that is external to the ego-vehicle. After the predicted trajectories are generated, the method continues by determining that at least one road agent predicted trajectory both (1) exists behind an object, indicating travel behind the object, and (2) overlaps with the object, when displayed on the user interface showing a driver's perspective view. The method includes modifying the at least one road agent predicted trajectory to remove the overlap. The method then proceeds with updating a display of the user interface to include any modified road agent predicted trajectory. Systems include a trajectory-prediction module to execute the methods.

Abstract: An image display device includes: an external sensor data acquisition unit acquired external sensor data detected at a first time point; an internal sensor data acquisition unit acquired internal sensor data detected at the first time point; a determination unit determined a position of the vehicle at a second time point that is a future time point after a predetermined time has elapsed from the first time point, based on the internal sensor data at the first time point; and a display control unit displayed a monitoring image indicating surroundings of the vehicle on the display unit based on the external sensor data at the first time point, wherein, the display control unit superimposes an object indicating the position of the vehicle at the second time point at the position on the monitoring image corresponding to the position of the vehicle at the second time point.

Abstract: A cargo area door control system for a vehicle is provided. The vehicle includes at least one cargo area and at least one cargo area door configured to be movable to enable physical access to the at least one cargo area, and movable to block physical access to the at least one cargo area. The control system includes one or more processors and a memory communicably coupled to the one or more processors. The memory stores a cargo area door control module including instructions that when executed by the one or more processors cause the one or more processors to determine if the vehicle currently resides at a selected destination and, responsive to a determination that the vehicle currently resides at the selected destination, operate a cargo area door unlocking mechanism to unlock the at least one cargo area door.

Abstract: A vehicle cargo area door control system for a vehicle including at least one cargo area and at least one cargo area door. The control system includes one or more processors and a memory communicably coupled to the processors for storing a cargo area door control module. The door control module operates to, responsive to the generation or receipt of an instruction which will cause the vehicle to start moving, determine if all vehicle cargo area doors are closed. If at least one cargo area door is not closed, command(s) are generated to close the at least one cargo area door.