Abstract: A vehicle, and a system and method for operating the vehicle. The system includes a sensor and a processor. The sensor obtains a detection set related to an object at a range from the vehicle. The processor is configured to select a convolution path for the detection set based on a range of the object, wherein the convolution path includes one or more convolutional layers and a number of the one or more convolutional layers is dependent on the range of the object, apply the one or more convolutional layers of the selected convolution path to the detection set to generate a filtered data set, and operate the vehicle with respect to the object using the filtered data set.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system includes a processing device programmed to receive a plurality of images representative of an environment of the host vehicle. The environment includes a road on which the host vehicle is traveling. The at least one processing device is further programmed to analyze the images to identify a target vehicle traveling in a lane of the road different from a lane in which the host vehicle is traveling; analyze the images to identify a lane mark associated with the lane in which the target vehicle is traveling; detect lane mark characteristics of the identified lane mark; use the detected lane mark characteristics to determine a type of the identified lane mark; determine a characteristic of the target vehicle; and determine a navigational action for the host vehicle based on the determined lane mark type and the determined characteristic of the target vehicle.

Abstract: Method and systems for generating vehicle motion planning model simulation scenarios are disclosed. The system receives a base simulation scenario with features of a scene through which a vehicle may travel. The system then generates an augmentation element with a simulated behavior for an object in the scene by: (i) accessing a data store in which behavior probabilities are mapped to object types to retrieve a set of behavior probabilities for the object; and (ii) applying a randomization function to the behavior probabilities to select the simulated behavior for the object. The system will add the augmentation element to the base simulation scenario at the interaction zone to yield an augmented simulation scenario. The system will then apply the augmented simulation scenario to an autonomous vehicle motion planning model to train the motion planning model.

Abstract: In some implementations, a vehicle device may receive, from a controller area network (CAN) bus of a vehicle and for a time period, messages received by the CAN bus after an engine of the vehicle is turned on. The vehicle device may combine identifiers provided in unique addresses, of the messages received by the CAN bus, to generate a unique identifier, and may utilize the unique identifier to determine data identifying a year, a make, and a model of the vehicle. The vehicle device may utilize the data identifying the year, the make, and the model of the vehicle to determine non-standard parameter identifiers associated with an engine control module of the vehicle.

Abstract: A system that may include multiple driving related systems that are configured to perform driving related operations; a selection module; multiple fault collection and management units that are configured to monitor statuses of the multiple driving related systems and to report, to the selection module, at least one out of (a) an occurrence of at least one critical fault, (b) an absence of at least one critical fault, (c) an occurrence of at least one non-critical fault, and (d) an absence of at least one non-critical fault; and wherein the selection module is configured to respond to the report by performing at least one out of: (i) reset at least one entity out of the multiple fault collection and management units and the multiple driving related systems; and (ii) select data outputted from a driving related systems.

Abstract: Aspects of the present disclosure include systems, methods, and devices to facilitate pick-up/drop-off zone (PDZ) handoffs between autonomous vehicles. Consistent with some embodiments, a pick-up/drop-off zone (PDZ) is located based on detecting a first autonomous vehicle stopped at a stopping location. A system determines, based on one or more criteria, whether to request the first autonomous vehicle to remain stopped at the stopping location to create an opportunity for a second autonomous vehicle to claim the PDZ. An amount of time for the first autonomous vehicle to remain stopped at the stopping location is determined based on the one or more criteria. A request to remain stopped at the stopping location is transmitted to a vehicle autonomy system of the first autonomous vehicle based on satisfaction of the one or more criteria. The request specifies the amount of time for the first autonomous vehicle to remain at the stopping location.

Abstract: A server includes a unit obtaining a position of a registered vehicle, a unit obtaining a vehicle dispatch position, a unit determining a candidate vehicle based on the vehicle dispatch position and the position of the registered vehicle, a unit transmitting information regarding an autonomous driving function of the candidate vehicle to a user device, a unit receiving information for identifying a dispatch vehicle, and a unit transmitting a vehicle dispatch position to the dispatch vehicle. The user device includes a unit receiving the information regarding the autonomous driving function of the candidate vehicle, a unit displaying the information regarding the autonomous driving function of the candidate vehicle, an unit accepting a user operation for selecting the dispatch vehicle, and a unit transmitting the information for identifying the dispatch vehicle to the server.

Abstract: A first driving solution for a vehicle along a portion of a route is determined based on an agent detected in the vehicle's environment following a first trajectory of a plurality of possible trajectories. A switching time is determined for the vehicle to deviate from the first driving solution for a situation in which the agent is following a second trajectory of the plurality of possible trajectories. The first driving solution is revised such that the vehicle will be able to switch from the revised first driving solution to another driving solution at the switching time in case if the detected agent is following the second trajectory.

Abstract: According to one implementation of the present disclosure, a method for determining airspeed for an unpowered vehicle is disclosed. The method includes: determining first and second body-fixed load factor measurements; determining a body Z-force coefficient based on an angle-of-attack parameter; and determining an airspeed value based on the second body-fixed load factor measurement and the body Z-force coefficient.

Abstract: An autonomous vehicle capable of trajectory prediction may include a first sensor, a second sensor, a processor, a trajectory planner, a low-level controller, and vehicle actuators. The first sensor may be of a first sensor type and may detect an obstacle and a goal. The second sensor may be of a second sensor type and may detect the obstacle and the goal. The processor may perform matching on the obstacle detected by the first sensor and the obstacle detected by the second sensor, model an existence probability of the obstacle based on the matching, and track the obstacle based on the existence probability and a constant velocity model. The trajectory planner may generate a trajectory for the autonomous vehicle based on the tracked obstacle, the goal, and a non-linear model predictive control (NMPC). The low-level controller may implement the trajectory for the autonomous vehicle by driving vehicle actuators.

Abstract: Controlling a speed limit includes determining a virtual vehicle speed as being a lower one of a vehicle speed and a target limit speed, determining a virtual APS value as being a larger one of a first APS value and a second APS value, transitioning to a second mode at a point in time at which an actual APS value and the second APS value become different, when it is expected to transition to the second mode, among a first mode for sustaining a SOC of a battery at the target limit speed and the second mode for depleting the SOC, and determining a transmission gear position by applying the determined virtual vehicle speed and the determined virtual APS value to one of a first shifting pattern and a second shifting pattern.

Abstract: A server includes a unit obtaining a position of a registered vehicle, a unit obtaining a vehicle dispatch position, a unit determining a candidate vehicle based on the vehicle dispatch position and the position of the registered vehicle, a unit transmitting information regarding an autonomous driving function of the candidate vehicle to a user device, a unit receiving information for identifying a dispatch vehicle, and a unit transmitting a vehicle dispatch position to the dispatch vehicle. The user device includes a unit receiving the information regarding the autonomous driving function of the candidate vehicle, a unit displaying the information regarding the autonomous driving function of the candidate vehicle, an unit accepting a user operation for selecting the dispatch vehicle, and a unit transmitting the information for identifying the dispatch vehicle to the server.

Abstract: The invention relates to a method for generating a dynamic speed profile of a motor vehicle which is suitable for simulating in particular actual vehicle operation on a route, comprising the following procedural steps: determining a route-based static speed profile for the route resolved into route segments based on information from a digital map; determining a route-based dynamized speed profile on the basis of the route-based static speed profile which factors in a defined maximum target deceleration to reach mandatory speed minima of the speed profile; determining a time-based dynamic speed profile resolved into time increments on the basis of the route-based dynamized speed profile, wherein an applied acceleration is determined in each time increment based on the speed dictated by the speed profile in a route segment corresponding to the respective time increment and the applied speed in the time increment; and outputting the time-based dynamic speed profile.

Abstract: A moving vehicle according to the present disclosure includes a chair frame including universal casters, a sitting seat disposed above the chair frame and connected to the chair frame, and a driving unit disposed below the sitting seat and connected to the chair frame so that the driving unit can rotate about a unit connection shaft, in which the driving unit includes a driving wheel including a rotation shaft located at a position deviated from a central axis of the unit connection shaft, a velocity detection unit configured to detect a rotational velocity of the driving wheel, and a driving control unit configured to control a velocity of the driving wheel according to an external driving force applied to the driving wheel.

Abstract: Disclosed is an operating method of a vehicle control apparatus controlling autonomous driving based on a vehicle external object including performing primary object detection based on a first vehicle external image received from a camera to obtain first object information, setting a first reflective area for reflection light based on the first object information, generating a second vehicle external image, in which a reflective image inside the first reflective area is removed from the first vehicle external image, using pixel values inside the first reflective area, performing secondary object detection based on the second vehicle external image to obtain second object information, determining reliability of the second object information based on information about the reflective image and the second object information, and controlling the autonomous driving of the vehicle based on the second object information when the reliability of the second object information is higher than a setting value.

Abstract: A computer includes a processor and a memory, the memory including instructions executable by the processor to predict a collision time between a corner point of a host vehicle and a target vehicle, predict a reach time for the corner point of the host vehicle to reach the target vehicle based on a predicted relative heading angle between the host vehicle and the target vehicle, and determine a threat number based on the lower of the collision time and the reach time.

Abstract: A method for calculating a time to contact of an autonomous vehicle, the method comprising: obtaining a plurality of event data an image, wherein the event data is associated with a pixel associated with a change in light intensity; determining a reference signal frequency associated with a transmitted light; identifying a select event data from the plurality of event data, wherein the light frequency associated with the select event data is substantially the same as the reference signal frequency; determining an object based on the select event data, wherein the object is fully enclosed by a bounding box comprising coordinates of a rectangular border; calculating a distance between a set of coordinates of the bounding box closest to the autonomous vehicle and the autonomous vehicle; and calculating the time to contact between the set of coordinates of the bounding box and the autonomous vehicle.

Abstract: A method for determining a minimum state of charge for an energy storage means of a vehicle can include: determining a routine of use of charge of the energy storage means; determining a user requirement for future driving of the vehicle; predicting a reduction in the state of charge of the energy storage means associated with the user requirement in dependence on the determined routine; determining a minimum state of charge for the energy storage means for enabling the user requirement to be satisfied in dependence on the predicted reduction; and providing an output to the user indicative of a time requirement for increasing the state of charge of the energy storage means to a value at or above the minimum state of charge.

Abstract: An autonomous vehicle incorporating a multimodal multi-technique signal fusion system is described herein. The signal fusion system is configured to receive at least one sensor signal that is output by at least one sensor system (multimodal), such as at least one image sensor signal from at least one camera. The at least one sensor signal is provided to a plurality of object detector modules of different types (multi-technique), such as an absolute detector module and a relative activation detector module, that generate independent directives based on the at least one sensor signal. The independent directives are fused by a signal fusion module to output a fused directive for controlling the autonomous vehicle.

Abstract: Embodiments of the disclosure provide systems and methods for ballistically estimating vehicle data. The system may include a communication interface configured to receive a first vehicle measurement taken at a first time point and a second vehicle measurement taken at a second time point. The system may further include at least one processor. The at least one processor may be configured to estimate a first version of vehicle data at a first speed for each of the second time point and a plurality of intermediate time points between the first time point and the second time point based on the first vehicle measurement using a prediction model. The at least one processor may be further configured to compute a second version of vehicle data at a second speed for the second time point based on the second vehicle measurement. The first speed is faster than the second speed.