A system for determining a driving range of a vehicle includes an energy storage component to store electrical energy or fuel. The system further includes a power source to convert the electrical energy or fuel into mechanical power to propel the vehicle. The system further includes a memory to store map data including road speeds, altitude data, road grades, or stop information corresponding to at least one of stop signs or stop lights, and a first driver profile corresponding to driving behavior of a first driver. The system further includes an electronic control unit (ECU) designed to predict the driving range of the vehicle based on an amount of the at least one of the electrical energy or fuel remaining in the energy storage component, the map data, and the first driver profile. The system further includes an output device designed to output the driving range of the vehicle.

A method for obtaining reference signals for vehicle control systems, in function of a vehicle geographical position along a travel route, includes providing data relating to the vehicle and data relating to a route to travel, and determining a vehicle driving force reference signal and a vehicle speed reference signal through a first optimisation process configured to optimise the driving force along the travel route. An engaged gear reference signal, in function of the positions of the vehicle along the travel route, is determined through a second optimisation process configured to optimise fuel consumption of the vehicle along the travel route. The second optimisation process is subsequent to the first optimisation process, and the data relating to the travel route, as well as the driving force reference signal and the speed reference signal, is received as input, determined through the first optimisation process.

A system for controlling platooning by a following vehicle includes a main body of the following vehicle. The system further includes a pressure sensor located in or on the main body and configured to detect a pressure corresponding to a pressure wake from a leading vehicle. The system further includes an electronic control unit (ECU) located in or on the main body, coupled to the pressure sensor, and configured to determine an optimal distance from the following vehicle to the leading vehicle based on the detected pressure. The optimal distance corresponding to a distance at which drag applied to the following vehicle is reduced based on the pressure wake from the leading vehicle.

A system for controlling platooning by a following vehicle includes a sensor located in or on the following vehicle configured to detect data corresponding to a shape of a leading vehicle. The system further includes an electronic control unit (ECU) located in or on the following vehicle, coupled to the sensor, and configured to determine an optimal distance from the following vehicle to the leading vehicle based on the shape of the leading vehicle, the optimal distance corresponding to a distance at which drag applied to the following vehicle is reduced based on a pressure wake from the leading vehicle.

Devices, systems, and methods are provided for enhanced obstacle detection. A vehicle may detect a neighboring vehicle traveling on a first road in a first traffic direction in a vicinity of the vehicle. The vehicle may collect data associated with the neighboring vehicle using one or more sensors of the vehicle. The vehicle may determine a status of the neighboring vehicle at a geolocation of the neighboring vehicle based on the collected data. The vehicle may determine that a first road anomaly occurred at the geolocation based on the status of the neighboring vehicle. The vehicle may set a first flag indicating the first road anomaly. The vehicle may determine to take a first action based on the first flag.

Methods and systems of determining and controlling a vehicle travel speed on a roadway determine a grade of the roadway at defined intervals along the roadway; calculate a maximum straight line vehicle speed for each defined interval based on the determined grade and vehicle performance data; determine a radius of curvature and a superelevation of the roadway for each defined interval; determine a lateral friction coefficient for a vehicle/roadway system; calculate a maximum cornering vehicle speed for each defined interval based on the curvature, superelevation, and lateral friction coefficient; calculate the travel speed for each defined interval based on the maximum straight line vehicle speed and the maximum cornering vehicle speed; and control the speed of the vehicle so that it does not exceed the calculated travel speed for each defined interval.

In a method for operating a motor vehicle during an autonomous parking process it is proposed that during the autonomous parking process a first braking torque is applied automatically to at least a first wheel, and a second braking torque is applied automatically to at least a second wheel, that a slip of one of the wheels is inferred from a comparison of the rotational speed of the first wheel to which the first braking torque is applied with the rotational speed of the second wheel to which the second braking torque is applied, and that if a variable characterizing the slip reaches or exceeds a limiting value, an action is automatically triggered.

Systems and methods are provided for crowdsourcing a sparse map for autonomous vehicle navigation. In one implementation, a non-transitory computer-readable medium may include a sparse map for autonomous vehicle navigation along a road segment. The sparse map may include at least one line representation of a road surface feature extending along the road segment, each line representation representing a path along the road segment substantially corresponding with the road surface feature, and wherein the road surface feature is identified through image analysis of a plurality of images acquired as one or more vehicles traverse the road segment and a plurality of landmarks associated with the road segment.

The embodiment of the invention provides a predictive power control system for hybrid vehicles. The system is mainly specific to the application scenarios of long-distance freight heavy trucks. Based on the vehicle configuration parameters and the current operating conditions, and with the aid of a vehicle-mounted expressway electronic navigation three-dimensional map, the system can be used to accurately and real-timely predict the dynamic road load power time-space function within the range of tens of kilometers of the electronic horizon in front of the vehicle; an electric power shunt device is commanded through a vehicle controller, and the flow direction and amplitude of 100-kilowatt level electric power can be accurately and continuously adjusted among an engine-driven generator set, a battery pack and a driving motor within tens of milliseconds of system response time so that an engine works stably in the high efficiency area of the engine for a long time; and the road load transient power balance required by a vehicle dynamic equation can be met through hundreds of kilowatts of fast charging and discharging of the battery pack in real time. Compared with traditional diesel heavy trucks, the hybrid heavy truck has the advantage that the overall fuel consumption and emissions in real world operation are reduced greatly on the premise of ensuring the vehicle power, freight timeliness and driving safety.

In some examples, a controller determines a target condition of usage of a vehicle, and selects a parameter set from among a plurality of parameter sets based on the determined target condition of usage of the vehicle, the plurality of parameter sets corresponding to different conditions of usage of the vehicle, where each parameter set of the plurality of parameter sets includes one or more parameters that control adjustment of one or more respective adjustable elements of the vehicle. The controller transmits, to the vehicle, the selected parameter set to control a setting of the one or more adjustable elements of the vehicle.