Systems and methods for personalizing adaptive cruise control in a vehicle are disclosed herein. One embodiment collects vehicle-following-behavior data associated with a particular driver; trains a Gaussian Process (GP) Regression model using the collected vehicle-following-behavior data to produce a set of adaptive-cruise-control (ACC) parameters pertaining to the particular driver, the set of ACC parameters modeling learned vehicle-following behavior of the particular driver; generates an acceleration command for the vehicle based, at least in part, on the set of ACC parameters; applies a predictive safety filter to the acceleration command to produce a certified acceleration command that has been vetted for safety; and controls acceleration of the vehicle automatically in accordance with the certified acceleration command to regulate a following distance between a lead vehicle and the vehicle in accordance with the learned vehicle-following behavior of the particular driver.

A method and apparatus for defining a model to determine a corrected trajectory of a mobile device or vehicle and a method and apparatus for determined a corrected trajectory using a defined model are provided. The model for determining a corrected trajectory includes accessing ground truth location data for a selected pathway, determining a GNSS pathway of a mobile device or vehicle, determining an IMU pathway of a mobile device or vehicle, and calculating an aggregated displacement trajectory. The apparatus for defining the model includes a communication interface configured to receive a first and second pathway, a memory configured to store a model and ground truth location data, and a processor to train the model.

Disclosed herein are an apparatus and a method for autonomous vehicle negotiation based on Vehicle-to-Vehicle (V2V) communication, the method including requesting, by vehicles that enter a driving negotiation section, a driving negotiation token, acquiring, by a vehicle that enters the driving negotiation section first, among the entering vehicles, the driving negotiation token, performing driving negotiation based on whether the driving negotiation token is acquired, and returning, by a vehicle having acquired the driving negotiation token, the driving negotiation token when the vehicle arrives at a destination.

An approach is provided for identifying partitions associated with erratic pedestrian behaviors and their correlations to points of interest. For example, the approach involves receiving sensor data associated with a geographic area. The approach also involves based on the sensor data, determining pedestrian-behavior parameter(s) respectively for partition(s). Each respective partition of the partition(s) represents a respective subarea of the geographic area, a respective time period, or a combination thereof. The approach further involves identifying at least one erratic partition from the partition(s) based on determining that a respective pedestrian-behavior parameter associated with the at least one erratic partition deviates from a baseline pedestrian-behavior parameter by at least a threshold extent. The approach further involves determining a correlation of the at least one erratic partition to at least one map feature of a geographic database. The approach further involves providing the correlation as an output.

The disclosure relates to a method for making sensor data more robust to adversarial perturbations, wherein sensor data are obtained from at least two sensors, wherein the sensor data obtained from the at least two sensors are replaced in each case piecewise by means of quilting, wherein the piecewise replacement is carried out in such a way that the respectively replaced sensor data from different sensors are plausible relative to one another, and wherein the sensor data replaced piecewise are output.

A vehicle collects data of a plurality of to-be-detected barrier gate crossbars around the vehicle by using a sensor mounted on the vehicle, and transmits the data of the plurality of to-be-detected barrier gate crossbars to a processor; the processor determines data of a target barrier gate crossbar from the data of the plurality of to-be-detected barrier gate crossbars based on a pose of the target barrier gate crossbar, where the target barrier gate crossbar is a barrier gate crossbar of a lane on which the vehicle is located; and the processor determines a status of the target barrier gate crossbar based on the data of the target barrier gate crossbar, and controls, based on the status of the target barrier gate crossbar, the autonomous driving vehicle to pass through the target barrier gate crossbar.

The present disclosure provides system and methods for a vehicle infotainment system (VIS) to monitor physiological parameters of occupants of a vehicle. The VIS also monitors vehicle operating parameters. The VIS is able to detect when an occupant is experiencing a physiological condition and correlates the physiological condition to one or more vehicle operating parameters. In response to detecting a physiological condition and to determining the correlation, the VIS causes an action to occur in order to mitigate the physiological condition and/or to seek assistance for the physiological condition.

Systems and methods for an On-Demand Autonomy (ODA) service. The system includes a set of functional modules enabled for ODA service activities disposed in a follower vehicle (Fv) in communication with an ODA server that includes a user request module configured to receive request information from the Fv from the ODA server, and to process and communicate the request information to the schedule module; the schedule module configured to coordinate an arrival time information with the ODA server for pickup of the Fv based on the request information, and communicate the arrival time information to the schedule execution module; the schedule execution module configured to direct the Fv to a pickup point based on the arrival time information, and communicate the pickup point to the indication module; and the indication module configured to provide alerts to vehicles in the vicinity of the pickup of the Fv via the ODA service.

A system for associating perceived and mapped lane edges can include a processor and a memory. The memory includes instructions such that the processor is configured to receive a sensor data representing a perceived object; receive map data representing a map object; determine a cost matrix a cost matrix indicative of an association cost for associating the map object to the perceived object; compare the association cost with an association cost threshold; and associate the perceived object with the map object based on the association cost.

Systems and methods for an On-Demand Autonomy (ODA) service. The system includes a selection module of a leader vehicle (Lv) connected to an ODA server to determine whether to confirm a request for an on-demand autonomy (ODA) service which has been broadcast wherein the ODA service request includes control of a follower vehicle (Fv) to a requested location by creating a virtual link between the Lv and the Fv to configure a vehicle platoon to enable transport of the Fv by the Lv wherein the vehicle platoon is a linking of the Lv to the Fv via the virtual link to enable the Lv to assume the control of the Fv to the requested location.