A system and method includes an autonomous agent having a communication interface that enables the autonomous agent to communicate with a plurality of infrastructure sensing devices; a plurality of distinct health monitors that monitor distinct operational aspects of the autonomous agent; an autonomous state machine that computes a plurality of allowed operating states of the autonomous agent based on inputs from the plurality of distinct health monitors; a plurality of distinct autonomous controllers that generate a plurality of distinct autonomous control instructions; and an arbiter of autonomous control instructions that: collects, as a first input, the plurality of autonomous control instructions generated by each of the plurality of distinct autonomous controllers; collects, as a second input, data relating to the plurality of allowed operating state of the autonomous agent; and selectively enables only a subset of the autonomous control instructions to pass to driving components of the autonomous agent.

In one embodiment, a data processing system for an autonomous driving vehicle (ADV) includes a processor, and a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations. The operations include generating a station-time (ST) graph based on perception data obtained from one or more sensors of the ADV, the ST graph including representing a location of an obstacle at different points in time, obtaining a tensor based on the ST graph, the tensor including a plurality of layers, the plurality of layers including a first layer having data representing one or more obstacles on a path in which the ADV is moving, applying a machine-learning model to the plurality of layers of the tensor to generate a plurality of numerical values, the plurality of numerical values defining a potential path trajectory of the ADV, and determining a path trajectory of the ADV based on the plurality of numerical values.

A system and method includes an autonomous agent having a communication interface that enables the autonomous agent to communicate with a plurality of infrastructure sensing devices; a plurality of distinct health monitors that monitor distinct operational aspects of the autonomous agent; an autonomous state machine that computes a plurality of allowed operating states of the autonomous agent based on inputs from the plurality of distinct health monitors; a plurality of distinct autonomous controllers that generate a plurality of distinct autonomous control instructions; and an arbiter of autonomous control instructions that: collects, as a first input, the plurality of autonomous control instructions generated by each of the plurality of distinct autonomous controllers; collects, as a second input, data relating to the plurality of allowed operating state of the autonomous agent; and selectively enables only a subset of the autonomous control instructions to pass to driving components of the autonomous agent.

A control system (10) is suitable for use in one's own motor vehicle (12) and is set up and intended to determine the current driving situation of one's own motor vehicle (12) and other motor vehicles (28, 40) in the surroundings of one's own motor vehicle (12) by means of a surroundings sensor system and to assign the other motor vehicles (28, 40) to specific movement paths or not. The control system is set up and intended based on the surroundings data provided to determine at least one path property for a future movement path of one's own motor vehicle (12), based on the surroundings data provided for every other motor vehicle (28, 40) in the surroundings of one's own motor vehicle (12) and in relation to at least two reference points of the respective other motor vehicle (28, 40) to determine a state vector, to transform the respectively determined state vector for each of the other motor vehicles (28, 40) into path coordinates and based on the at least one path property for one's own motor vehicle (12) and, to determine based on the respective transformed state vector, a probability distribution of a position of each of the other motor vehicles (28, 40) corresponding to each of the at least two reference points of the respective other motor vehicle (28, 40).

Techniques are discussed for controlling a vehicle, such as an autonomous vehicle, to navigate a junction in an environment. In some cases, the techniques can be used to navigate a turn at the junction or traverse through the junction. Operations include the vehicle detecting a stop signal and preparing the vehicle to stop at a location associated with the junction. The vehicle can determine a time to execute a maneuver and a visibility distance that a sensor can observe in the environment. A speed of the vehicle to execute the maneuver can be determined based on the time to execute the maneuver and the visibility distance.

Systems for vehicles are disclosed using simplified state machines. For one example, a data processing system for a vehicle includes a plurality of subsystem nodes interconnected by a network topology. Each subsystem node includes a transceiver and micro-controller coupled to the transceiver. The micro-controller is configured to obtain an atomic machine state bit vector. Each bit of the atomic bit vector describes a state of the vehicle used by a state machine operating within the vehicle. The micro-controller multiplies a first bit vector mask with the atomic machine state bit vector to obtain a first result. The first result identifies first states of interest. The micro-controller determines a next state for the state machine based on the identified first states of interest. The micro-controller performs a function for the vehicle based on the determined next state. The atomic machine state bit vector can be updated based on the determined next state and distributed within the vehicle.

Autonomous control of a subject vehicle including a longitudinal motion control system includes determining states of parameters associated with a trajectory for the subject vehicle and parameters associated with a control reference determined for the subject vehicle. A range control routine is executed to determine a first parameter associated with a range control command based upon the states of the plurality of parameters, and a speed control routine is executed to determine a second parameter associated with a speed control command based upon the states of the plurality of parameters. An arbitration routine is executed to evaluate the range control command and the speed control command, and operation of the subject vehicle is controlled to achieve a desired longitudinal state, wherein the desired longitudinal state is associated with a minimum of the range control command and the speed control command.

A vehicle sound effect generation apparatus includes a running state detecting unit that detects a running state of a vehicle; a lateral input amount setting unit that sets, based on the running state detected by the running state detecting unit, a lateral input amount in which a physical amount relating to at least one of a movement of the vehicle in a width direction and a movement of the vehicle in a turning direction is a parameter; an adjustment wave sound selector that selects one or more integer-order adjustment wave sounds having an integer-order frequency component, based on the lateral input amount; and a sound effect generation unit that synthesizes a fundamental wave sound having a fundamental frequency component with the one or more integer-order adjustment wave sounds selected.

An apparatus includes a sensor, a navigation circuit and a control circuit. The sensor may be configured to generate surrounding road information of a road. The road may have a plurality of available lanes. The navigation circuit may be configured to determine a current position of the apparatus on the road. The control circuit may be configured to (i) access map data that identifies a number of the available lanes in the road proximate the position, (ii) determine a current lane among the available lanes that the apparatus is within based on all of the position, the surrounding road information and the map data and (iii) generate feedback data based on both the position and the current lane. The navigation device may be further configured to adjust the current position to a center of the current lane in response to the feedback data.

A system for a host vehicle and includes a memory and a vehicle control module. The memory stores autonomous status bits for each local vehicle. The autonomous status bits indicate whether the corresponding local vehicle is operating in a non-autonomous, semi-autonomous, or fully autonomous mode. The vehicle control module: generates autonomous status bits indicative of an autonomous status level of the host vehicle and transmits the autonomous status bits in a message to first vehicle communication devices; determines that local vehicles are in a local environment of the host vehicle; receives messages including the autonomous status bits of the local vehicles from second vehicle communication devices; and unless operating in a fully autonomous mode, generates a request for a driver of the host vehicle to take control of the host vehicle based on the autonomous status bits of the host vehicle and the local vehicles.