Abstract: This document describes techniques and systems for selecting a parking space using a probabilistic approach. An example system includes a processor that can determine whether multiple parking spaces are available in proximity to a host vehicle using sensor data. Parking-space characteristics (e.g., a width, entry turning radius, and longitudinal distance to the parking space) of each available parking space are determined using the sensor data. The processor can then choose a selected parking space among the multiple parking spaces based on the parking-space characteristics. The processor or another processor can then control the host vehicle to park in the selected parking space using an assisted-driving or autonomous-driving system. In this way, the described system can select and navigate to a parking space using a probabilistic approach. The processor can choose the parking space and parking maneuver based on programmable and customizable parking-space characteristics in some implementations.

Abstract: The techniques and systems herein enable ESA modification based on manual steering inputs. Specifically, a score is determined for a manual steering input to a host vehicle while an ESA is actively applying an ESA steering input to the host vehicle. The score quantifies an amount of additional steering input relative to the ESA steering input (e.g. additional steering angle, steering wheel torque). The ESA steering input is maintained, modified, or canceled based on the score. By doing so, the system is able to effectively adapt the ESA to the manual steering inputs thereby allowing for effective collision mitigation while ensuring that the vehicles operate as intended by the drivers.

Abstract: Techniques and systems are described that enable evasive steering assist (ESA) with a pre-active phase. An ESA system predicts that a collision with an object is imminent and enters a pre-active phase. The pre-active phase causes a required drop in steering force to occur prior to determining that the collision is imminent. At a later time, the ESA system determines that the collision is imminent and enacts an active phase. The active phase causes a steering force effective to avoid the collision. By enacting the pre-active phase prior to the determination of the imminent collision, the ESA system may provide the additional steering force needed to avoid the collision without delay while simultaneously shielding a driver of vehicle from feeling the drop in steering force.

Abstract: Evasive steering assist (ESA) systems and methods for a vehicle utilize a set of vehicle perception systems configured to detect an object in a path of the vehicle, a driver interface configured to receive steering input from a driver of the vehicle via a steering system of the vehicle, a set of steering sensors configured to measure a set of steering parameters, and a controller configured to determine a set of driver-specific threshold values for the set of steering parameters, compare the measured set of steering parameters and the set of driver-specific threshold values to determine whether to engage/enable an ESA feature of the vehicle, and in response to engaging/enabling the ESA feature of the vehicle, command the steering system to assist the driver in avoiding a collision with the detected object.

Abstract: A vehicle control system includes a controller circuit in communication with a steering sensor and one or more perception sensors. The steering sensor is configured to detect a steering torque of a steering wheel of a host vehicle. The one or more perception sensors are configured to detect an environment proximate the host vehicle. The controller circuit is configured to determine when an operator of the host vehicle requests a take-over from fully automated control of the host vehicle based on the steering sensor. The controller circuit classifies the take-over request based on the steering sensor.

Abstract: A method of providing evasive steering assist (ESA) includes storing yaw rate data related to a host vehicle, wherein yaw rate data includes a yaw rate stored at each time step from an initial time step [0] to a current time step [n]. The method further includes determining whether to initiate ESA, wherein in response to a determination to initiate ESA, the method includes calculating a current position, a current heading angle, a destination position, and a destination heading angle, wherein the stored yaw rate data is utilized to determine the current heading angle and the destination heading angle. The method further includes generating an evasive steering assist (ESA) output based on the current position, the current heading angle, the destination position, and the destination heading angle.

Abstract: Techniques and systems are described that enable evasive steering assist (ESA) with a pre-active phase. An ESA system predicts that a collision with an object is imminent and enters a pre-active phase. The pre-active phase causes a required drop in steering force to occur prior to determining that the collision is imminent. At a later time, the ESA system determines that the collision is imminent and enacts an active phase. The active phase causes a steering force effective to avoid the collision. By enacting the pre-active phase prior to the determination of the imminent collision, the ESA system may provide the additional steering force needed to avoid the collision without delay while simultaneously shielding a driver of vehicle from feeling the drop in steering force.

Abstract: Techniques and systems are described that enable evasive steering assist (ESA) with a pre-active phase. An ESA system predicts that a collision with an object is imminent and enters a pre-active phase. The pre-active phase causes a required drop in steering force to occur prior to determining that the collision is imminent. At a later time, the ESA system determines that the collision is imminent and enacts an active phase. The active phase causes a steering force effective to avoid the collision. By enacting the pre-active phase prior to the determination of the imminent collision, the ESA system may provide the additional steering force needed to avoid the collision without delay while simultaneously shielding a driver of vehicle from feeling the drop in steering force.

Abstract: A system includes an inertial navigation system module (INS module) that detects vehicle yaw rates and vehicle lateral speeds, a controller circuit communicatively coupled with the INS module. The controller circuit determines a tire cornering stiffness (Cf, Cr) based on vehicle physical parameters and vehicle dynamic parameters. The controller circuit determines a vehicle moment of inertia (Iz) based on the vehicle physical parameters, the vehicle dynamic parameters, and the tire cornering stiffness (Cf, Cr).

Abstract: Techniques and systems are described that enable evasive steering assist (ESA) with a pre-active phase. An ESA system predicts that a collision with an object is imminent and enters a pre-active phase. The pre-active phase causes a required drop in steering force to occur prior to determining that the collision is imminent. At a later time, the ESA system determines that the collision is imminent and enacts an active phase. The active phase causes a steering force effective to avoid the collision. By enacting the pre-active phase prior to the determination of the imminent collision, the ESA system may provide the additional steering force needed to avoid the collision without delay while simultaneously shielding a driver of vehicle from feeling the drop in steering force.

Abstract: A system includes an inertial navigation system module (INS module) that detects vehicle yaw rates and vehicle lateral speeds, a controller circuit communicatively coupled with the INS module. The controller circuit determines a tire cornering stiffness (Cf, Cr) based on vehicle physical parameters and vehicle dynamic parameters. The controller circuit determines a vehicle moment of inertia (Iz) based on the vehicle physical parameters, the vehicle dynamic parameters, and the tire cornering stiffness (Cf, Cr).

Abstract: Provided is a non-belt automatic mechanized sampling system for a train, including: a working platform provided with a slide rail; a sampling mechanism slidably arranged on the slide rail and configured to collect materials from the carriage of the train; an integrated sample preparation component including a discharging mechanism and a feeder, a crusher, a constant mass dividing machine and a sample retention barrel arranged from top to bottom. The feeder transports the material to the crusher. The crusher crushes the material and transports the crushed material to the constant mass dividing machine. The constant mass dividing machine divides the crushed material into samples to the sample retention barrel, and the discarded material to the discharging mechanism. The discharging mechanism transports the discarded materials to the carriage.

Abstract: A vehicle control system includes a controller circuit in communication with a steering sensor and one or more perception sensors. The steering sensor is configured to detect a steering torque of a steering wheel of a host vehicle. The one or more perception sensors are configured to detect an environment proximate the host vehicle. The controller circuit is configured to determine when an operator of the host vehicle requests a take-over from fully automated control of the host vehicle based on the steering sensor. The controller circuit classifies the take-over request based on the steering sensor.

Abstract: A system includes a controller circuit configured to monitor, while a host vehicle is operated in a manual driving mode, a speed change response of an operator of the host vehicle based on a movement of a first vehicle traveling on a roadway, identify at least one speed parameter based on the speed change response, and apply, when the host vehicle is controlled in an autonomous driving mode, the at least one speed parameter based on the movement of a second vehicle traveling on the roadway.

Abstract: A system includes a controller circuit configured to monitor, while a host vehicle is operated in a manual driving mode, a speed change response of an operator of the host vehicle based on a movement of a first vehicle traveling on a roadway, identify at least one speed parameter based on the speed change response, and apply, when the host vehicle is controlled in an autonomous driving mode, the at least one speed parameter based on the movement of a second vehicle traveling on the roadway.

Abstract: A system includes an inertial navigation system module (INS module) that detects vehicle yaw rates and vehicle lateral speeds, a controller circuit communicatively coupled with the INS module. The controller circuit determines a tire cornering stiffness (Cf, Cr) based on vehicle physical parameters and vehicle dynamic parameters. The controller circuit determines a vehicle moment of inertia (k) based on the vehicle physical parameters, the vehicle dynamic parameters, and the tire cornering stiffness (Cf, Cr).

Abstract: LED decorative light comprising DC power supply, main controller, and LED light chains; said main controller consists of key switch, crystal oscillating access circuit, and main control chip, with said key switch and crystal oscillating access circuit connected to said main control chip respectively; said main control chip pulse width modulation end outputs variable duty ratio PWM; said crystal oscillating circuit is used to provide instruction cycle required for main control chip; and said key switch is used to control operating state of main control chip; wherein said main controller also includes a voltage adjustment circuit, used to adjust DC power supply voltage to the value required for LED light chains, with input end of this circuit connected to said DC power supply, its control end connected to pulse width modulation end of said main control chip, and its output end connected to LED light chain input end.

Abstract: LED decorative light comprising DC power supply, main controller, and LED light chains; said main controller consists of key switch, crystal oscillating access circuit, and main control chip, with said key switch and crystal oscillating access circuit connected to said main control chip respectively; said main control chip pulse width modulation end outputs variable duty ratio PWM; said crystal oscillating circuit is used to provide instruction cycle required for main control chip; and said key switch is used to control operating state of main control chip; wherein said main controller also includes a voltage adjustment circuit, used to adjust DC power supply voltage to the value required for LED light chains, with input end of this circuit connected to said DC power supply, its control end connected to pulse width modulation end of said main control chip, and its output end connected to LED light chain input end.