Abstract: A behavior control method for controlling a behavior of a vehicle comprising: specifying a blind-spot region as blind-spot of an environment recognition portion along a travel route for the vehicle; determining a jump-out possibility of a moving object to the travel route from the blind-spot region; performing a possibility reduction behavior to lower the jump-out possibility, in response to that the jump-out possibility is confirmed; and performing a travel behavior compliant with the travel route after starting the possibility reduction behavior.

Abstract: In one aspect, a system for detecting worn or damaged components of an agricultural machine may include first and second acoustic sensors positioned at first and second locations on the agricultural machine, respectively, with the second location being spaced apart from the first location. A controller of the system may be configured to determine a first acoustic parameter associated with the first location of the agricultural machine based on acoustic data received from the first acoustic sensor. The controller may also be configured to determine a second acoustic parameter associated with the second location of the agricultural machine based on acoustic data received from the second acoustic sensor. Furthermore, the controller may be configured to determine a component of the agricultural machine is worn or damaged when the first acoustic parameter differs from the second acoustic parameter by a predetermined amount.

Abstract: A self-driving coordination system and the control method thereof are disclosed. The system and the control method are applied to an all-self-driving vehicle fleet. The self-driving coordination system comprises a leader control device, a follower control device, and a server. The leader control device is mounted in a leader. The follower control device is mounted in a follower. The leader control device and the follower control device communicate with each other for bidirectional data transmission. The server communicates with the leader control device and the follower control device for respective bidirectional data transmission.

Abstract: A robot configured for multi-robot pose estimation execute iteratively the primary particle filter and the secondary particle filter independently from each other to update the pose estimations in the primary and the secondary particles. In response to each encounter of the robot with a neighboring robot, the robot receives neighboring particles of a particle filter of the neighboring robot identifying poses and likelihoods of the poses of the neighboring robot and replaces the primary particles of the primary particle filter with the secondary particles fused with the neighboring particles. The robot outputs its pose according to the primary particles of the primary particle filter.

Abstract: Systems and methods are disclosed for dynamically adjusting effective sensor coverage coordinates of a sensor used to assist in navigating an autonomous driving vehicle (ADV) in response to environmental conditions that may affect the ideal operation of the sensor. An ADV includes a navigation system and a safety monitor system that monitors some, or all, of the navigation system, including monitoring: dynamic adjustment of effective sensor coverage coordinates of a sensor and localization of the ADV within a high-definition map. The ADV safety monitor system further determines safety-critical objects surrounding the ADV, determines safe areas to navigate the ADV, and ensures that the ADV navigates only to safe areas. An automated system performance monitor determines whether to pass-through ADV navigation control commands, limit one or more control commands, or perform a fail-operational behavior, based on the ADV safety monitor systems.

Abstract: The present disclosure provides a data transmission method and a data transmission device for an intelligent driving vehicle, and a device. The method includes: acquiring data to be transmitted; encoding the data to be transmitted to generate encoded data; generating a check digit according to the data to be transmitted; adding the encoded data to a data packet, wherein a trailer of the data packet comprises the check digit; and transmitting the data packet.

Abstract: A method for navigating a vehicle through a predefined path in an environment. The predefined path includes a plurality of predefined points. The method includes generating a distance database, enabling the predefined path by enabling each of the plurality of predefined points, navigating the vehicle to a first point, and navigating the vehicle from the first point to a second point. The distance database is associated with the predefined path. The first point and the second point are located on the predefined path. Navigating the vehicle from the first point to the second point includes repeating an iterative navigation process until a termination condition is satisfied. The termination condition includes a total traveled distance of the vehicle obtained from odometer data of the vehicle exceeding a termination threshold.

Abstract: A vehicle controller device is provided including a travel control section configured to control autonomous driving and remote driving, a biometric information acquisition section configured to acquire biometric information of an occupant, a state determination section configured to determine, based on the biometric information acquired by the biometric information acquisition section, whether or not an abnormality predicted state has arisen in which manual driving by operation by the occupant is predicted to become compromised and also whether or not an abnormal state has arisen in which manual driving is compromised, a notification section configured to notify an operation device of a determined state in cases in which either the abnormality predicted state or the abnormal state is determined to have arisen, and a reception section capable of receiving operation-ready information indicating that operation by a remote operator is possible from the operation device in response to the notification.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining respective importance scores for a plurality of agents in a vicinity of an autonomous vehicle navigating through an environment. The respective importance scores characterize a relative impact of each agent on planned trajectories generated by a planning subsystem of the autonomous vehicle. In one aspect, a method comprises providing different states of an environment as input to the planning subsystem and obtaining as output from the planning subsystem corresponding planned trajectories. Importance scores for the one or more agents that are in one state but not in the other are determined based on a measure of difference between the planned trajectories.

Abstract: An approach is provided for path recovery when using map-based dynamic location sampling. The approach, for instance, involves initiating a capture of a current location of a vehicle on a road segment by a location sensor based on a keep-alive sampling rate. The location sensor is configured to operate at a sampling rate that is reduced from a default sampling rate in addition to the keep-alive sampling rate. The approach also involves determining a predicted location of the vehicle based on an estimated time of arrival of the vehicle at an end node of the road segment. The estimated time of arrival is based on historical traversal time data for the road segment. The approach further involves reconfiguring the location sensor to operate at the default sampling frequency based on determining that the predicted location differs from the current location by more than a threshold distance.

Abstract: According to an aspect of an embodiment, operations may comprise for each of the set of geographic X-positions, accessing an HD map of a geographical region surrounding the geographic X-position, determining a convergence range for the geographic X-position, and storing the convergence range for the geographic X-position in the HD map. The operations may also comprise accessing the HD map, predicting a next geographic X-position of a target vehicle, predicting a covariance of the predicted next geographic X-position, accessing the convergence range for the geographic X-position in the HD map closest to the predicted next geographic X-position, estimating a current geographic X-position of the target vehicle by performing a localization algorithm, and determining a confidence value for the estimated current geographic X-position of the target vehicle based on the predicted next geographic X-position, the predicted covariance, and the accessed convergence range.

Abstract: A method for controlling a vehicle based on a driver-centric model is presented. The method includes generating a trajectory for the vehicle and receiving an input from a driver. The method also includes generating a velocity profile and an acceleration profile based on a combination of the trajectory and the input. The method further includes controlling the vehicle based on the velocity profile and the acceleration profile.

Abstract: A method for estimating a yaw (or heading) of a rotating body of a machine is disclosed. The method may include obtaining measurements related to a velocity of a global navigation satellite system (GNSS) antenna coupled to the rotating body based on a motion state associated with the machine satisfying one or more conditions, calculating a first unit vector of a lever arm from a rotation axis to the GNSS antenna, and calculating a second unit vector orthogonal to the one or more measurements related to the velocity of the GNSS antenna in a direction towards the rotation axis (e.g., based on a velocity of another GNSS antenna coupled to the rotating body and/or a yaw rate measurement obtained by an inertial measurement unit). Accordingly, the yaw of the rotating body may be estimated based on a rotation angle between the first unit vector and the second unit vector.

Abstract: The driving support device executes self-position estimation of an own vehicle by odometry. In the case where landmarks around the own vehicle are detected, the driving support device corrects the self-position and creates an environment map. Next, the driving support device estimates the correction accuracy of the estimated self-position. In the case where the correction accuracy is high, the driving support device selects a first operating mode of driving support. In the case where the correction accuracy is low and the accuracy of odometry is also low, the driving support device selects a second operating mode of driving support. The second operating mode is a mode in which the degree of driving support is lower than that in the first operating mode.

Abstract: Techniques and methods for securing vehicle systems. For instance, an authorization system may store data representing frequencies at which destination locations are associated pick-up locations for a fleet of autonomous vehicles. The authorization system may then receive a request for an autonomous vehicle to pick up a passenger at a first location and drop off the passenger at a second location. Based on the first location and the second location, the authorization system may determine a frequency for the request. The authorization system may then determine whether a control system for the fleet of autonomous vehicles is compromised based on whether the frequency is less than or equal to a threshold frequency. If the authorization system determines that the control system is compromised, the authorization system may perform a remedial action, such as notifying a teleoperator.

Abstract: It is provided a method for enabling remote control of a vehicle with autonomous propulsion capability. The method is performed by a vehicle data provider and comprises: detecting a need for manual assistance of the vehicle by an operator being remote from the vehicle; obtaining a stream of vehicle data, the vehicle data relating to a time prior to when remote control starts; modifying the vehicle data, which comprises adjusting a duration of playback of the vehicle data; providing the modified vehicle data for playback to the operator; providing, once the playback of modified vehicle data has ended, vehicle data in real-time to the operator; and enabling remote control of the vehicle by the operator.

Abstract: A method, a system, and a computer program product are provided for updating one or more attributes of a learned road sign (LRS). The system, for example, comprising at least one non-transitory memory configured to store computer program code instructions; and at least one processor is configured to execute the computer program code instructions to obtain sensor data associated with the LRS and determine a plurality of first downstream links associated with the LRS, based on the sensor data. Further, the at least one processor is configured to select a candidate downstream link from the plurality of first downstream links based on a heading difference between the LRS and each of the plurality of first downstream link and to update the one or more attributes of the LRS, based on the candidate downstream link.

Abstract: Systems and methods for operating a driveline of a hybrid vehicle are disclosed. In one example, output of an electric machine is adjusted after commanding reactivation of all engine cylinder valves that have been deactivated. The electric machine torque may counteract the engine producing torque that is greater than a requested torque due to high intake manifold pressure.

Abstract: Methods, systems, and computer program products are provided. Aspects include determining characteristic data associated with a physical environment, based on the characteristic, determining an elastic map for the physical environment, wherein the elastic map comprises a graph comprising a set of nodes and a set of edges, wherein each edge connects two nodes and a set of configurable parameters that define an elastic coupling for each edge, determining an initial physical configuration of the set of nodes in the physical environment based on the elastic map, causing a set of mobile sensors to establish the initial configuration in the physical environment, simulating a mobile sensor elastic coupling between each mobile sensor based on the elastic energy function for each edge, collecting an environmental data point associated with the physical environment, and adjusting a configuration of the set of mobile sensors based on the environmental data point.

Abstract: The control device of hybrid vehicle 1 comprises an output control part 41 configured to control outputs of the internal combustion engine 10 and the motor 16, a target SOC setting part 42 configured to set a target state of charge, and an arrival rate calculating part 43 configured to calculate a probability of the hybrid vehicle reaching the charging station. When the hybrid vehicle is being driven outside the charging station, the output control part is configured to control outputs of the internal combustion engine and the motor so that a state of charge of the battery when the hybrid vehicle reaches the charging station becomes the target state of charge. The target SOC setting part is configured to lower the target state of charge when the probability is relatively high compared to when the probability is relatively low.