A calibration system calibrates inertial sensor readings on a vehicle. The calibration system estimates an attitude of the ground from a series of height and position measurements and reads an attitude from an inertial sensor subsystem attached to the vehicle. The calibration system then calculates an attitude offset between the vehicle and inertial sensor subsystem based on a difference between the estimated attitude of the ground and the attitude reading of the inertial sensor subsystem. The calibration system may estimate a slope of the ground from a 3-dimensional terrain map. The slope of the ground is converted into an estimated roll and/or pitch of the vehicle which is then compared with the roll and pitch readings from the inertial sensor subsystem to determine the attitude offset.

The present invention determines at least one dangerous driving indicator by use of a physical model based on the dynamics of a vehicle. According to the invention, a dynamic model of the vehicle determines a slip parameter of the vehicle, which deduces a representative dangerous driving indicator.

A system and method for adjusting engine settings and/or calibrations is based on engine and/or vehicle parameters, and/or environmental conditions, and is further based upon a forecasted drive cycle, forecasted driving condition, vehicle vocation, vehicle geographic location, vehicle load, type of operation, season of the year, vehicle system or subsystem condition and/or operation, and/or other factors. An engine of the vehicle has an ECU configured to store and implement an engine control map. At least one algorithm is operable to determine an engine control map specific to an engine operating parameter, a vehicle operating parameter, an environmental condition, and/or an expected range of settings and calibrations. At least one device is configured to wirelessly upload to the vehicle the specific engine control map, and then load or flash the specific engine control map to the ECU.

A vehicle (10) has a camera recognition system to detect and interpret a road sign (14) indicative of a gradient. A gradient related shift map of an automatic vehicle transmission is pre-selected upon recognition of the road sign, and implemented upon detection that the gradient has commenced. The invention provides for rapid and consistent implementation of a suitable shift map on a gradient.

A system includes a power source to generate power to propel the vehicle, and a speed sensor to detect a current speed. The system also includes a camera to detect image data corresponding to a current roadway, and a GPS sensor to detect location data corresponding to a current location of the vehicle. The system also includes an ECU. The ECU is designed to determine a target vehicle speed based on at least one of the image data or the location data. The ECU is also designed to calculate an energy-efficient acceleration pattern to accelerate the vehicle from the current speed to the target vehicle speed based on a goal to minimize energy usage of the power source. The ECU is also designed to control the power source to accelerate the vehicle from the current speed to the target vehicle speed using the energy-efficient acceleration pattern.

A determination method for a drive force to be requested for a hybrid vehicle, and an apparatus. The determination method comprises the following steps: obtaining a gear state, a current vehicle speed, a current gas pedal degree of engagement, and drive force mapping information of a vehicle, the drive force mapping information indicating a correspondence relationship between vehicle speed, gas pedal degree of engagement, and drive force; if the gear state is such that the vehicle is not in park gear or neutral gear, obtaining a driving mode and altitude data of the vehicle; and if the altitude data is less than a preset altitude, determining a drive force to be requested for the vehicle on the basis of the current vehicle speed, the current gas pedal degree of engagement, the driving mode, and the drive force mapping information.

A system and method for adjusting engine settings and/or calibrations is based on engine and/or vehicle parameters, and/or environmental conditions, and is further based upon a forecasted drive cycle, forecasted driving condition, vehicle vocation, vehicle geographic location, vehicle load, type of operation, season of the year, vehicle system or subsystem condition and/or operation, and/or other factors. An engine of the vehicle has an ECU configured to store and implement an engine control map. At least one algorithm is operable to determine an engine control map specific to an engine operating parameter, a vehicle operating parameter, an environmental condition, and/or an expected range of settings and calibrations. At least one device is configured to wirelessly upload to the vehicle the specific engine control map, and then load or flash the specific engine control map to the ECU.

A method for processing point clouds having variable spatial distributions of scan lines includes receiving a point cloud frame generated by a sensor configured to sense a vehicle environment. Each of the points in the frame has associated two-dimensional coordinates and an associated parameter value. The method also includes generating a normalized point cloud frame by adding interpolated points not present in the received frame, at least by, for each interpolated point, identifying one or more neighboring points having associated two-dimensional coordinates that are within a threshold distance of two-dimensional coordinates for the interpolated point, and calculating an estimated parameter value of the interpolated point using, for each of the identified neighboring points, a distance between the two-dimensional coordinates and the parameter value associated with the identified neighboring point. The method also includes generating, using the normalized point cloud frame, signals descriptive of a current state of the vehicle environment.

A method for controlling a vehicle based on sensor data having variable sensor parameter settings includes receiving sensor data generated by a vehicle sensor while the sensor is configured with a first sensor parameter setting. The method also includes receiving an indicator specifying the first sensor parameter setting, and selecting, based on the received indicator, one of a plurality of neural networks of a perception component, each neural network having been trained using training data corresponding to a different sensor parameter setting. The method also includes generating signals descriptive of a current state of the environment using the selected neural network and based on the received sensor data. The method further includes generating driving decisions based on the signals descriptive of the current state of the environment, and causing one or more operational subsystems of the vehicle to maneuver the vehicle in accordance with the generated driving decisions.

A method for configuring a perception component of a vehicle having one or more sensors includes generating a first set of training data that includes first sensor data corresponding to a first setting of one or more sensor parameters, and an indicator of the first setting. The method also includes generating a second set of training data that includes second sensor data corresponding to a second setting of the sensor parameter(s), and an indicator of the second setting. The method further includes training the perception component, at least by training a machine learning based model using the first and second training data sets. The trained perception component is configured to generate signals descriptive of a current state of the vehicle environment by processing sensor data generated by the sensor(s), and one or more indicators indicating which setting of the sensor parameter(s) corresponds to which portions of the generated sensor data.