A method includes identifying route data including a threshold arrival time for a route for an autonomous vehicle (AV) and calculating, based on the route data and a fuel-efficient speed value for each segment of the route, an estimated arrival time. Responsive to the estimated arrival time not meeting the threshold arrival time, the method includes identifying at least a subset of segments that each represent a candidate for speed increase, computing, for each segment in the subset and based on the fuel economy data, a correlation metric that indicates a correlation between a change in fuel economy and a change in speed for a corresponding segment in the subset, and increasing, for at least one segment from the subset and based on a respective correlation metric, a fuel-efficient speed value of the corresponding segment from the subset to provide a speed profile reflecting the increased fuel-efficient speed value.

A controller of an autonomous traveling vehicle as an information processing apparatus of the disclosure executes acquiring first information relating to a predetermined item and the first information relating to predetermined processing in a processing apparatus mounted on the autonomous traveling vehicle, acquiring second information relating to shipping of the predetermined item, controlling running of the autonomous traveling vehicle based on the second information, and controlling the operation of the processing apparatus based on the first information when the autonomous traveling vehicle is in a running state based on the second information.

The subject disclosure relates to ways to improve route duration calculations e.g., estimated time of arrival (ETA) approximations, by taking consideration of reroute probabilities along a given vehicle path. In some aspects, the disclosed technology encompasses a process including steps for identifying a route between a first destination to a second destination, determining a reroute likelihood associated with at least one AV maneuver along the route, and calculating an estimated time of arrival (ETA) based on the reroute likelihood associated with at least one AV maneuver. Systems and machine-readable media are also provided.

A method may include identifying computing systems corresponding to an autonomous vehicle (AV) in which each computing system is configured to perform at least one operation relating to driving the AV. The method may include determining whether the computing systems use a first respective real-world parameter as an input to any of the operations or generate a second respective real-world parameter as an output of the operations. A respective operation corresponding to a respective computing system may be designated for accelerated performance based on the determination, and the operations of the computing systems may be performed. A first operation not designated for accelerated performance may include first computations corresponding to the first operation after waiting for a synchronization delay period, and a second operation designated for accelerated performance may include second computations corresponding to the second operation and performed without waiting for the synchronization delay period.

A vehicle management system comprising a server and a user terminal for managing a vehicle with an autonomous driving function, the terminal device includes a terminal communication unit which transmits a user position information indicating the user's present position to the server through telecommunications network, and the server communication unit that receives the vehicle location information indicating the present position of the vehicle and a vehicle management unit for setting a boarding point at which the user rides the vehicle and for managing traveling of the vehicle by adjusting, in accordance with the present position of the user and the position of the vehicle with respect to the boarding point, a time at which the vehicle arrives at the boarding point.

The subject disclosure relates to ways to improve route duration calculations e.g., estimated time of arrival (ETA) approximations, by taking consideration of reroute probabilities along a given vehicle path. In some aspects, the disclosed technology encompasses a process including steps for identifying a route between a first destination to a second destination, determining a reroute likelihood associated with at least one AV maneuver along the route, and calculating an estimated time of arrival (ETA) based on the reroute likelihood associated with at least one AV maneuver. Systems and machine-readable media are also provided.

Various technologies described herein relate to routing an autonomous vehicle based upon likelihood of interacting with a disruptive third-party vehicle. A computing system receives an origin location of an autonomous vehicle and a destination location of the autonomous vehicle. The computing system identifies a route for the autonomous vehicle to take based upon output of a computer-implemented model. The computer-implemented model is generated based upon labeled data that is indicative of observed instances of a disruptive third-party vehicle exhibiting behavior that impacts operation of an autonomous vehicle. The output of the computer-implemented model is a score that is indicative of a likelihood that the disruptive third-party vehicle will be traveling through a geographic location along a candidate route at a certain time. The score is used in part to identify the route from amongst a plurality of candidate routes. The autonomous vehicle then travels along the route.

A method, system and product for user-based ethical decision making by a self-driving vehicle. The method comprises determining an ethical preference for the self-driving vehicle based on an ethical preference of a controlling entity that is controlling over the self-driving vehicle. The ethical preference of the controlling entity is obtained based on responses of the controlling entity to an ethical questioner. The method further comprises selecting a selected outcome between two potential alternative outcomes. The selection is performed based on the ethical preference for the self-driving vehicle, and causing the self-driving vehicle to perform the selected action, whereby causing the selected outcome.

A control device includes a travel controller configured to cause a mobile object to travel autonomously. The travel controller controls the mobile object such that a behavior in which control details for the mobile object do not change even if travel conditions of a conditions-varying travel path in which the travel conditions vary according to a time period vary is performed.

A control system interface for a vehicle includes a primary processing unit and a secondary processing unit. The primary processing unit is configured to receive and process a trajectory generated by a trajectory computing unit for autonomous control of the vehicle. The secondary processing unit is configured to receive the trajectory concurrently with the primary processing unit, and to process the trajectory. Autonomous control of the vehicle is passed from the primary processing unit to the secondary processing unit in response to a fault condition with the primary processing unit.