A method, apparatus, and system for planning a deceleration trajectory based on a natural deceleration profile for an autonomous driving vehicle (ADV) is disclosed. In one embodiment, in response to a request for driving in a natural deceleration mode, a current speed of the ADV is determined. A speed guideline is generated based on a predetermined natural deceleration profile associated with the ADV in view of the current speed of the ADV. A speed planning operation is performed by optimizing a total cost function based on the speed guideline to determine speeds of a plurality of trajectory points along a trajectory planned to drive the ADV. A number of control commands are generated based on the speed planning operation to control the ADV with the planned speeds along the trajectory, such that the ADV naturally slows down according to the predetermined natural deceleration profile.

A vehicle includes an axle, an electric machine, a first wheel, a second wheel, a first friction brake, a second friction brake, and a controller. The controller is programmed to, in response to and during an anti-locking braking event, generate first and second signals indicative of a braking torque demand at the first and second wheels, respectively, based on a difference between a desired wheel slip ratio and an actual wheel slip ratio of the first and second wheels, respectively, adjust a regenerative braking torque of the electric machine based on a product of the first signal and a regenerative braking weighting coefficient, adjust a first friction braking torque based on a product of the first signal and a friction braking weighting coefficient, and adjust a second friction braking torque based on the second signal and dynamics of the first and second output shafts.

A system for controlling the speed of a vehicle. The system includes a satellite receiver configured to determine a satellite navigation-based speed of the vehicle and one or more speed sensors configured to determine a sensor-based speed of the vehicle. The system further includes a controller having one or more electronic processors and in communication with the satellite receiver and the one or more speed sensors. The controller is configured to receive a desired set speed from a user, determine an actual speed of the vehicle based on the satellite navigation-based speed and the sensor-based speed, and control the vehicle such that the actual speed of the vehicle is equal to the desired set speed.

An energy storage and transmission system (ESRS) (69) comprises a transmission (9, 11) and an energy storage device such as a flywheel (1). While energy is being transferred between the energy storage device (1) and an energy source/sink (7), the transmission ratio of the transmission (9, 11) will usually be changing constantly. In order to manage the torque applied by the energy transfer device (1) or the power transferred, a controller (100) responds to discrepancy between the torque or power supplied and the torque or power demanded.

A method for determining a reference driving class of a driver from among a set of predetermined driving classes, each predetermined driving class being characterized by a speed profile, comprises the following steps: The speed of a driver over a given journey is determined, the observed speed is compared with the speed profiles of each of the predetermined driving classes so as to obtain a deviation between the driver and each of the driving classes, a detected driving class is determined as being that which minimizes this deviation, and the reference driving class is determined as a function of this detected driving class.

Presented are model-based control systems for operating parallel hybrid powertrains, methods for making/using such systems, and motor vehicles with parallel hybrid powertrains and model-based torque and speed control capabilities. A method for controlling operation of a hybrid powertrain includes receiving a command signal for a hybrid powertrain operation associated with a driver input and a current operating mode of the powertrain. A desired output torque for executing the powertrain operation is then determined. The method determines if a speed differential between an engine speed of an engine and a torque converter output speed of a torque converter is less than a calibrated threshold; if so, the method responsively engages a clutch device to operatively connect the engine's output member to the transmission's input member. Engine torque is then coordinated with motor torque such that the sum of the engine and motor torques is approximately equal to the desired output torque.

Methods and systems for operating a hybrid driveline that includes an engine and an electric machine are presented. In one non-limiting example, the engine and electric machine are operated according to a solution of a Hamiltonian that includes a first co-state and a second co-state, an engine fuel flow parameter, a rate of change of battery state of charge parameter, and an emissions flow rate parameter.

Simulating output of a perception system may comprise receiving scenario data indicating a position associated with a simulated sensor and a position and/or identifier of an object, and instantiating a three-dimensional representation of an environment and the object (i.e., a simulated environment). The system may generate depth data indicating distances and/or positions of surfaces in the simulated environment relative to the simulated sensor position and determine a three-dimensional region of interest based at least in part on the depth data associated with at least a portion of the object. In some examples, the three-dimensional region of interest may be smaller than a size of the object, due to an occlusion by topology of the simulated environment and/or another object in the simulated environment.

Aspects and implementations of the present disclosure address shortcomings of existing technology by enabling autonomous vehicle simulations based on retro-reflection optical data. The subject matter of this specification can be implemented in, among other things, a method that involves initiating a simulation of an environment of an autonomous driving vehicle, the simulation including a plurality of simulated objects, each having an identification of a material type of the respective object. The method can further involve accessing simulated reflection data based on the plurality of simulated objects and retro-reflectivity data for the material types of the simulated objects, and determining, using an autonomous vehicle control system for the autonomous vehicle, a driving path relative to the simulated objects, the driving path based on the simulated reflection data.

Methods, apparatuses, and computer-readable media are described. In one example, a method of controlling a vehicle comprises: receiving, using one or more sensors, a first set of measurements of a set of physical attributes of the vehicle in a motion; determining, based on a motion data model that defines a set of relationships among the set of physical attributes of the vehicle in the motion and based on the first set of measurements, a set of expected measurements of the set of physical attributes; determining whether to use an entirety of the first set of measurements to control an operation of the vehicle based on comparing the first set of measurements and the set of expected measurements; and responsive to determining not to use the entirety of the first set of measurements, controlling the operation of the vehicle based on a second set of measurements.