A transportation system controls a fleet of autonomous vehicles to implement passenger transportation and coordinate delivery of baggage or other associated items using separate vehicles. The transportation system receives passenger data and associated item data via a user interface, and determines the number and type of autonomous vehicles to transport the passengers and items from selected pick-up locations to a destination. In various implementations, the transportation system may support different pick-up locations, pick-up times and/or delivery times for the passengers and associated items. The transportation system also may determine delayed item delivery options for different delivery times and modes of transportation. Based on the passenger and item data, along with input received via the user interface, the transportation system determines the vehicles to deploy and the delivery routes, and transmits instructions to the autonomous vehicles to provide the passenger transportation and perform the item delivery.

An approach is provided for using a passenger-based driving profile. The approach involves detecting an identity of a user of a vehicle. The approach also involves retrieving a passenger profile of the user based on the identity. The passenger profile is generated based on sensor data indicating a reaction of the user to at least one vehicle driving behavior previously experienced by the user as a vehicle passenger. The approach further involves configuring the vehicle based on the passenger profile.

A traffic control system for an automatic driving vehicle includes a vehicle control system and a management and control system. The management and control system collects snow removal information by a snow removal information collector, and calculates traveling environment information of the snow-removed area by a snow-removed area traveling environment information calculator. The vehicle control system performs, by a first automatic driving controller, first automatic driving control that is made redundant by a control system based on map information and location information and by a control system based on external environment recognition information. The vehicle control system performs, by a second automatic driving controller, second automatic driving control that is made redundant by a control system based on the location information and the map information corrected using the traveling environment information of the snow-removed area and by a control system based on the external environment recognition information.

An information processing device that controls a mobile object including lodging equipment with a plurality of compartments performs: creating an operation schedule including a first period in which movement for allowing a plurality of users to ride in or alight from the mobile object is a main purpose and a second period in which riding and alighting of the users are not required based on lodging requests acquired from the plurality of users; and generating an operation instruction for executing different controls on the mobile object in the first period and the second period and transmitting the operation instruction to the corresponding mobile object.

A passenger vehicle optical communication system includes a source vehicle including a light source and an endpoint vehicle including a camera. The source vehicle transmits a series of patterns using the light source to communicate, as one example, state information to the endpoint vehicle.

An autonomous vehicle can obtain state data associated with an object in an environment, obtain map data including information associated with spatial relationships between at least a subset of lanes of a road network, and determine a set of candidate paths that the object may follow in the environment based at least in part on the spatial relationships between at least two lanes of the road network. Each candidate path can include a respective set of spatial cells. The autonomous vehicle can determine, for each candidate path, a predicted occupancy for each spatial cell of the respective set of spatial cells of such candidate path during at least a portion of a prediction time horizon. The autonomous vehicle can generate prediction data associated with the object based at least in part on the predicted occupancy for each spatial cell of the respective set of spatial cells for at least one candidate path.

Systems and methods for controlling autonomous vehicles are provided. Assisted autonomy tasks facilitated by operators for a plurality of autonomous vehicles can be tracked in order to generate operator attributes for each of a plurality of operators. The attributes for an operator can be based on tracking one or more respective assisted autonomy tasks facilitated by the operator. The operator attributes can be used to facilitate enhanced remote operations for autonomous vehicles. For example, request parameters can be obtained in response to a request for remote assistance associated with an autonomous vehicle. An operator can be selected to assist with autonomy tasks for the autonomous vehicle based at least in part on the operator attributes for the operator and the request parameters associated with the request. Remote assistance for the first autonomous vehicle can be initiated, facilitated by the first operator in response to the request for remote assistance.

A method for controlling an autonomous vehicle includes using one or more computing devices to transmit a request for a trip. The trip is from a pickup location to a destination location. The method also includes determining the autonomous vehicle for the trip is within a predetermined distance from the pickup location, providing a set of component controls to receive user input at a user interface after the determining. The set of component controls includes interactive controls for identifying or accessing the autonomous vehicle. A first user input is received at the user interface for one or more of the set of component controls, and control instructions for the autonomous vehicle based on the first user input are transmitted.

The disclosure generally relates to autonomous or semi-autonomous driving vehicles. An exemplary embodiment of the disclosure relates to a system to provide one or more threat vectors to a cluster of vehicles. An exemplary vehicle detection system includes a communication module configured to receive a first threat vector from a first vehicle in a cluster of vehicles. The first threat vector may include a plurality of primary attributes associated with a moving object. The vehicle detection system may also include a detector module configured to detect the moving object and to provide one or more secondary attributes associated with the moving object; and a controller to construct a second threat vector as a function of one or more of the first threat vector, the primary attributes and the secondary attributes associated with the moving object.

A remote driving service processing device includes: a general user terminal by which a requester applies for a remote driving service for moving a vehicle to a destination; a remote control terminal by which a remote driver remotely control the vehicle and sends a remote driving service termination permission request for terminating the remote driving service when the vehicle is having difficulty reaching the destination; and a server that sends a termination approval to the remote control terminal and terminates the remote driving service when (i) transferring the remote driving service termination permission request received from the remote control terminal to the general user terminal, and (ii) receiving a remote driving service termination consent, which is a response to the remote driving service termination permission request, from the general user terminal.