A system and a method for autonomous decisioning and operation by an autonomous agent includes: collecting decisioning data including: collecting a first stream of data includes observation data obtained by onboard sensors of the autonomous agent, wherein each of the onboard sensors is physically arranged on the autonomous agent; collecting a second stream of data includes observation data obtained by offboard infrastructure devices, the offboard infrastructure devices being arranged geographically remote from and in an operating environment of the autonomous agent; implementing a decisioning data buffer that includes the first stream of data from the onboard sensors and the second stream of data from the offboard sensors; generating current state data; generating/estimating intent data for each of one or more agents within the operating environment of the autonomous agent; identifying a plurality of candidate behavioral policies; and selecting and executing at least one of the plurality of candidate behavioral policies.

Disclosed are an autonomous vehicle and a pedestrian guidance system and method using the same. The pedestrian guidance system according to an embodiment of the present invention includes at least one autonomous vehicle for transmitting pedestrian information recognizing a pedestrian and indicating the pedestrian based on a signal received from the pedestrian terminal to other vehicle. At least one of an autonomous vehicle, a user terminal, and a server of the present invention may be connected to or fused with an Artificial Intelligence (AI) module, a drone (Unmanned Aerial Vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, and a device related to a 5G service.

System, methods, and other embodiments described herein relate to dynamically determining an appropriate responsive action for a moving vehicle that encounters a roadside pedestrian and stationary vehicle. In one embodiment the disclosed system identifies a stationary vehicle in an environment of a subject vehicle based at least in part on information from a plurality of sensors disposed on the subject vehicle and determines a classification for the stationary vehicle as valid or abandoned based at least in part on the information from the plurality of sensors. A classification of valid indicates that the subject vehicle is recommended to undertake an action relative to the stationary vehicle. The disclosed generates a score based at least in part on the classification, the score indicating a recommended trajectory modification for the subject vehicle, and modifies a trajectory of the subject vehicle based on score.

A driving support device performs steering control and deceleration control for avoiding an object which is detected in front of a host vehicle. The driving support device performs: calculating a target lateral distance which is a target of the steering control and which is a lateral distance between the host vehicle and the object when the host vehicle passes by the object; and increasing target deceleration which is a target of the deceleration control and which is deceleration of the host vehicle when the host vehicle passes by the object as a lateral distance restraint value which is obtained by subtracting the target lateral distance from a threshold value increases when the target lateral distance is less than the threshold value.

According to an embodiment, an information processing device includes a memory and one or more hardware processors electrically coupled to the memory and configured to function as a change unit, and a display controller. The change unit is configured to change a reference path to a position at a lateral distance when the lateral distance obtained from lateral environmental information indicating a lateral environment of the reference path referred to as a scheduled running path of a moving body is larger than a distance from a lateral end to a center of a running region of the moving body. The display controller is configured to display display information including the reference path on a display unit.

A method for localization of a vulnerable road user (VRU) includes receiving a received signal strength indication (RSSI) level of a wireless signal of a mobile device carried by the VRU detected by a wireless sensor in an area of interest. The detected RSSI level is compared to RSSI fingerprints stored in a fingerprinting database (DB) so as to identify an RSSI fingerprint having a closest match to the detected RSSI level. The VRU is localized at a position stored in the fingerprinting DB for the identified RSSI fingerprint.

A driving assist device for a vehicle sets a a roadway area ahead of the vehicle, detects an avoidance target existing ahead of the vehicle, and executes collision avoidance control that avoids a collision between the vehicle and the avoidance target. The collision avoidance control is more likely to be executed when the avoidance target is within the roadway area than when the avoidance target is outside the roadway area. The driving assist device detects a roadway end object and a first lane marking of a first lane in which the vehicle exists. An imaginary position is a position apart from the detected position of the roadway end object toward the first lane by a constant distance. The driving assist device sets the imaginary position or the detected position of the the first lane marking as a boundary position of the roadway area based on a predetermined condition.

As an example, data identifying characteristics of a road user as well as contextual information about the vehicle's environment is received from the vehicle's perception system. A prediction of the intent of the object including an action of a predetermined list of actions to be initiated by the road user and a point in time for initiation of the action is generated using the data. A prediction of the behavior of the road user for a predetermined period of time into the future indicating that the road user is not going to initiate the action during the predetermined period of time is generated using the data. When the prediction of the behavior indicates that the road user is not going to initiate the action during the predetermined period of time, the vehicle is maneuvered according to the prediction of the intent prior to the vehicle passing the object.

Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. For instance, that the vehicle is approaching a crosswalk may be determined. A set of segments may be identified for the crosswalk. A set of potential occluded pedestrians may be generated. Each potential occluded pedestrian of the set is assigned a speed characteristic and a segment. The segments of the set of potential occluded pedestrians may be updated over time using the assigned speed characteristics. Sensor data from a perception system of the vehicle is received, and one or more potential occluded pedestrians an having an updated assigned segment corresponding to a segment that is visible to a perception system of the vehicle may be removed from the set of potential occluded pedestrians. After the removing, the set may be used to control the vehicle in the autonomous driving mode.

An autonomous vehicle control system includes one or more processors. The one or more processors are configured to cause a transmitter to transmit a transmit signal from a laser source. The one or more processors are configured to cause a receiver to receive a return signal reflected by an object. The one or more processors are configured to cause one or more optics to generate a first polarized signal of the return signal with a first polarization, and generate a second polarized signal of the return signal with a second polarization that is orthogonal to the first polarization. The one or more processors are configured to operate a vehicle based on a ratio of reflectivity between the first polarized signal and the second polarized signal.