Another computer implemented method for estimating lanes for a vehicle may include the following steps carried out by computer hardware components: determining measurement data at a location of the vehicle using a sensor mounted at the vehicle; transforming the measurement data of the sensor into a global coordinate system to obtain transformed measurement data; and estimating lanes at the location for the vehicle based on the transformed measurement data.

A method of generating an output trajectory of an ego vehicle is described. The method includes extracting high-level features from a bird-view image of a traffic environment of the ego vehicle. The method also includes generating, using an automaton generative network, an automaton including an automaton state distribution describing a behavior of the ego vehicle in the traffic environment according to the high-level features. The method further includes generating the output trajectory of the ego vehicle according to extracted bird-view features of the bird-view image and the automaton state distribution describing the behavior of the ego vehicle in the traffic environment.

Various embodiments include methods and systems for managing vehicle behavior. In some embodiments, a vehicle processor of the first vehicle may receive dynamic traffic flow feature information relevant to movements of a second vehicle within a predetermined proximity to the host vehicle, determine probabilities of a plurality of potential behaviors of the second vehicle based on the received dynamic traffic flow feature information, predict a future path of the second vehicle, and use the predicted future path of the second vehicle in a vehicle control function. In some embodiments, the vehicle processor of the first vehicle may predict a behavior of a third vehicle based on received intention information about the second vehicle, and may adjust a behavior of the first vehicle based on the predicted behavior of the third vehicle.

A method for fuel efficiency optimization by predictive driving, the method comprises: determining a current state of a vehicle and current state of an environment of the vehicle; estimating a future state of the vehicle and a future state of the environment of the vehicle; wherein a future state of each one of the vehicle and the environment is a state at a future point of time following a current point of time; evaluating, whether the vehicle has to change one or more vehicle progress parameters between the current point of time and the future point of time; selecting a future driving behavior out of multiple future driving behaviors, that will implement the change of the one or more vehicle progress parameters, wherein the selecting is based on a fuel consumption associated with the change of the one or more future driving parameters; and generating at least one of a selected future driving behavior suggestion, a selected future driving behavior alert, and a selected future driving behavior command.

A mobile telecommunications device for providing an in-vehicle driver warning system during a vehicle journey using sensed driving information and local traffic information is described. The mobile telecommunications device comprises: a sensor set comprising at least one of an image sensor, an audio sensor, a geographic positioning sensor and an accelerometer; a user interface for receiving user input; a processor operatively connected to the sensor set and the user interface; a wireless communications module for communicating with a remote server, the wireless communications module being operatively connected to the processor; the processor, through its connection to the user interface, determining, during the vehicle journey, using the inputs received by the user interface, or through its connection to the sensor set, using sensor data received from the sensor set, a start of a driving period during which the mobile device is removably installed to the vehicle and the vehicle is in use; the processor, through its connection to the sensor set, using the sensor data received from the sensor set during the driving period to derive, in use, the sensed driving information associated with how the vehicle is driven; the processor, through its connection to the wireless communications module, receiving the local traffic information obtained from the wireless communications module, the local traffic information concerning other vehicles in the vicinity of the mobile telecommunications device; the processor using, in use, the local traffic information and the driving information and determining if the current relative position and speed of the vehicle exceeds a threshold profile; and wherein the processor generates, in use, a warning signal if the current relative position and speed of the vehicle exceed the threshold profile, and, through its connection to the user interface, transmits the warning signal to the user interface for warning the driver of the vehicle.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for agent behavior prediction using keypoint data. One of the methods includes obtaining data characterizing a scene in an environment, the data comprising: (i) context data comprising data characterizing historical trajectories of a plurality of agents up to the current time point; and (ii) keypoint data for a target agent; processing the context data using a context data encoder neural network to generate a context embedding for the target agent; processing the keypoint data using a keypoint encoder neural network to generate a keypoint embedding for the target agent; generating a combined embedding for the target agent from the context embedding and the keypoint embedding; and processing the combined embedding using a decoder neural network to generate a behavior prediction output for the target agent that characterizes predicted behavior of the target agent after the current time point.

The present invention provides a vehicle control device capable of improving fuel consumption while reducing deterioration of emission by appropriately controlling a powertrain system of a vehicle. A vehicle control device includes: a prediction unit configured to predict speeds or accelerations of a vehicle based on a plurality of prediction models; a fuel consumption information calculation unit configured to calculate fuel consumption for each of a plurality of prediction results obtained by the prediction unit; a selection unit configured to select any one of the plurality of prediction results; and a powertrain control unit configured to control at least one of an engine, a generator, an inverter, a drive motor, and a transmission of the vehicle based on the prediction result selected by the selection unit.

A method of operating an autonomous vehicle includes detecting, based on an input received from a sensor of an autonomous vehicle that is being navigated by an on-board computer system, an occurrence of a driving event, making a determination by the on-board computer system, upon the detecting the occurrence of the driving event, whether or how to alter the path planned by the on-board computer system according to a set of rules, and performing further navigation of the autonomous vehicle based on the determination until the driving event is resolved. The driving event may include a presence of an object in a shoulder area of the road. The driving event may include accumulation of more than a certain number of vehicles behind the autonomous vehicle. The driving event may include a slow vehicle ahead of the autonomous vehicle. The driving event may include a do-not-change-lane zone is within a threshold.

A method for assembling a vehicle from a set of modules for travelling a planned route, wherein the set of modules comprises at least one functional module and a plurality of drive modules. Each drive module comprises a pair of wheels, electrical motor, and an interface releasably connectable to a corresponding interface on another module, wherein each drive module is configured to operate autonomously and has an individual set of energy parameters. The method comprising obtaining route information associated with route segments of the planned route, selecting a first drive module having an individual set of energy parameters matching route information associated with a first route segment and selecting a second drive module having an individual set of energy parameters matching route information associated with a second route segment, and thereafter commanding the drive modules to connect together and with a functional module.

The present disclosure relates to adaptive cruise control in the field of automatic driving, and discloses a vehicle control method, an apparatus, an electronic device and a storage medium. A specific implementation is: firstly, determining a target travelling scenario according to real-time monitoring data upon fulfilment of a preset update condition; then, determining a target time headway according to the target travelling scenario, where the target time headway is used to dynamically adjust a relative motion state between an host vehicle and a surrounding vehicle; and finally, controlling a vehicle according to the target time headway. It solves the problem of the prior art in overemphasizing the state of the vehicle ahead for automatic driving control while overlooking the perception of the driver or passenger of the host vehicle in the travelling scenario can prompt the driver to manually intervene, compromising the experience of the automatic driving.