A vehicle includes a control unit. The control unit is configured to execute: outputting, when detecting or estimating travel inability of an own vehicle, information regarding a request for receiving an article provided from another vehicle to avoid the travel inability. The control unit performs, when determining that a request vehicle outputs the information regarding the request, a prescribed process for providing an article corresponding to the request to the request vehicle.

A method for controlling an autonomous vehicle including: obtaining trip information of a current trip of a user of the autonomous vehicle and historical traffic information related to the current trip; selecting an autonomous driving (AD) mode that is suitable for the current trip from a plurality of pre-defined AD modes; comparing time required for the autonomous vehicle to complete a portion of the current trip in the selected AD mode with historical average time to complete the portion of the current trip, the historical average time being acquired based on the historical traffic information; and dynamically adjusting driving of the autonomous vehicle based on the comparison to minimize the difference between the time required for the autonomous vehicle to complete the portion of the current trip in the selected AD mode and the historical average time.

A dispatch device includes an information acquisition unit that acquires, for each of a plurality of vehicles, location information indicating a location of the vehicle and loaded object information indicating a status of an object of transportation loaded on the vehicle and a vehicle dispatching unit that dispatches an unfilled vehicle that can carry an object of transportation so that a predetermined number or higher number of unfilled vehicles, are present around an operating vehicle that is carrying an object of transportation.

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 control device for an automated driving vehicle has a first automated driving mode in which the automated driving vehicle, receiving a permission notice from an operations management controller, travels, according to automatic operation, along a controlled route managed by the operations management controller, in accordance with a traveling schedule provided from the operations management controller; and a second automated driving mode in which the automated driving vehicle travels, without a permission notice from the operations management controller, along a non-controlled route that is not managed by the operations management controller, according to automatic operation. The first automated driving mode and the second automated driving mode are switchable.

An early stopped traffic response system includes a distributed computing system controller programmed and/or configured to reduce travel time delays caused by predictable instances of traffic stoppage associated with common carrier traffic. An early stopped traffic response system may obtain the common carrier schedule and route associated with a first crossing point or intersection, predict an estimated arrival time for the common carrier vehicle at the intersection, and determine, based on the estimated arrival time at the intersection, a time delay associated with the common carrier vehicle crossing the intersection. The early stopped traffic response system may generate a navigation plan that reroutes the delayed vehicle in advance of arrival at the intersection by predicting the common carrier arrival time. Predictive analytics may determine arrival times using common carrier databases and/or observed real-time information received via infrastructure computing systems networks, a vehicle-to-vehicle (V2V) and/or vehicle-to-infrastructure (V2I), networks, among other sources.

A vehicle control system includes a recognizer that recognizes a surrounding environment of a vehicle, and a driving controller that performs speed control and steering control of the vehicle based on a recognition result of the recognizer. When moving the vehicle to a parking area after detecting that an occupant gets off the vehicle at a stop position, the driving controller adjusts a start timing for starting the vehicle based on the number of vehicles stopped at the stop position recognized by the recognizer.

The present disclosure provides a probabilistic decision engine for autonomous vehicles. Briefly described, one embodiment comprises taking a network connection matrix (based on maps and graph theory) and a cost matrix (with entries of the cost's mean values and probability distributions) as input and generates the probability distribution of optimal routes as output. The disclosed probabilistic decision engine comprises a stochastic network standardization module, a stochastic network decomposition module and a probabilistic optimization kernel. A deterministic network reduction method is first used to derive a standard reduced network, augmented by the stochastic network reduction. The standard network is then decomposed into a series of stochastic subnetworks by using the convolution, probability density function (PDF) shifting, and PDF reshaping techniques. A pure-analytical probabilistic solver is finally used to solve the stochastic optimization problem.

A method ensures that a vehicle can safely pass a traffic light. The vehicle includes a processor and a light sensor. The method includes receiving traffic data, establishing a speed profile, establishing a control distance, the processor establishing, in accordance with the speed profile, a control distance at which braking ensures that the vehicle stops safely before the position of the traffic light, adjustment according to the speed profile, detecting the state of the traffic light when the vehicle is at the control distance from the traffic light, and the processor activating braking if the traffic light is red.

A method for determining a movement trajectory (MT) for a movable object (a vehicle) in a rule-based trajectory planning (TP) system, TP being performed based on minimizing overall costs of a cost function (CF), the CF considering violation costs (VC) which arise for each MT section from a potential respective violation of violatable rules as to the section, the rule violation (RV) including a state/transition RV, the state RV indicating a violation of a state rule indicating an impermissible state of the object; the transition RV indicating a violation of a transition rule indicating an impermissible state transition, the state RV being assigned a time-dependent cost amount of the VC, and the transition RV being assigned a fixed, time-independent cost amount of the VC, so that overall costs for a MT for each section violating a violatable rule depend on the time-dependent/fixed cost amount assigned to the violated rule.