Apparatus, systems, and methods to capture and combine patient vitals and image data are disclosed. An example apparatus includes an imaging device to capture imaging data of a patient; a patient monitor to capture non-imaging data of the patient; and a communication interface between the imaging device and the patient monitor to route the non-imaging data to the imaging device. The example imaging device is to combine the non-imaging data with the imaging data to form a combined data set to be processed to determine a clinical outcome.

The vehicle control device: controls the drive device and the braking device such that an actual acceleration representing an actual acceleration of the vehicle coincides with a target acceleration for driving the vehicle so that the vehicle stops at a preset target stop position; acquires the target acceleration every time a predetermined time elapses, and sets the target acceleration to a value such that the magnitude of the change amount does not exceed the threshold change amount when the magnitude of the change amount representing the difference between the target acceleration and the previous target acceleration exceeds the threshold change amount; and sets the threshold change amount to a larger value than when the emergency condition is not satisfied in a case where a predetermined emergency condition is satisfied in a case where a driving force or a braking force larger than in a normal state is required.

The present disclosure adds automotive millimeter-wave (mmWave) radars to the current perception system and makes them an effective augmentation for ultrasonic sensors (USSs). Relying on the superior range and Doppler resolution, mmWave radars generate denser point clouds than the intersection detections of USSs, making it possible to form a more robust and accurate radar occupancy grid. The radar occupancy grid can be formulated as a polygon with multiple nodes. Thus,, the memory-consuming occupancy grid is simplified as a polygon that consists of a bunch of points, which can be used in the downstream application for relieving computational burden. Radars measure and estimate the Doppler velocity of detected targets such that one can assign a moving velocity to each node of the radar polygon. This makes it possible to predict the shape of a future radar polygon and feed the predicted radar polygon to downstream applications.

Example systems and methods allow for reporting and sharing of information reports relating to driving conditions within a fleet of autonomous vehicles. One example method includes receiving information reports relating to driving conditions from a plurality of autonomous vehicles within a fleet of autonomous vehicles. The method may also include receiving sensor data from a plurality of autonomous vehicles within the fleet of autonomous vehicles. The method may further include validating some of the information reports based at least in part on the sensor data. The method may additionally include combining validated information reports into a driving information map. The method may also include periodically filtering the driving information map to remove outdated information reports. The method may further include providing portions of the driving information map to autonomous vehicles within the fleet of autonomous vehicles.

Example systems and methods allow for reporting and sharing of information reports relating to driving conditions within a fleet of autonomous vehicles. One example method includes receiving information reports relating to driving conditions from a plurality of autonomous vehicles within a fleet of autonomous vehicles. The method may also include receiving sensor data from a plurality of autonomous vehicles within the fleet of autonomous vehicles. The method may further include validating some of the information reports based at least in part on the sensor data. The method may additionally include combining validated information reports into a driving information map. The method may also include periodically filtering the driving information map to remove outdated information reports. The method may further include providing portions of the driving information map to autonomous vehicles within the fleet of autonomous vehicles.

Provided are systems and methods for vehicle control time delay compensation. Data associated with a vehicle state of the vehicle is provided. Data associated with at least one control parameter is received from the control system, the data generated by the control system based on the vehicle state. A time delay related to generation of the data associated with the at least one control parameter is determined by the control system, the time delay associated with a period of time from when the data associated with the vehicle state was transmitted to the control system to when the data associated with the at least one control parameter was received by the DBW system. A DBW parameter is determined based on the data associated with the at least one control parameter and the time delay, wherein the DBW parameter is used for traversal of a path by the vehicle.

A position estimation device of the present disclosure includes: a communication-method-based reception unit which receives signals transmitted in respective communication methods, by reception units corresponding to the communication methods; an own position calculation unit which calculates first position information of the mobile body per calculation cycle, using the transmitted signal; a movement amount calculation unit which calculates a movement amount of the mobile body per the calculation cycle; an autonomous navigation positioning unit which calculates second position information on the basis of the first position information calculated by the own position calculation unit and the movement amount calculated by the movement amount calculation unit, for each communication method; and an index value calculation unit which calculates, for each communication method, a variance value of difference values between the first position information and the second position information, as an index value.

The present disclosure provides a method comprising receiving a rideshare request from a user, the rideshare request including a destination; transporting the passenger to the destination using an autonomous vehicle (AV) having a plurality of windows comprising electrically switchable smart glass; during the transporting, monitoring a metric related to arrival of the AV at the destination; and untinting the windows when the monitored metric has a prescribed relationship to a threshold value.

A vehicle control device includes a scene determination unit determining whether or not a current traveling scene is a traveling-restricted scene, an order setting unit setting priorities corresponding to a restriction with respect to driving behaviors previously classified for different purposes in a case where it is determined that the traveling scene is the traveling-restricted scene and setting priorities with respect to the plurality of driving behaviors in a case where it is not determined that the traveling scene is the traveling-restricted scene, a traveling plan generating unit generating traveling plans corresponding to the plurality of priority-set driving behaviors, an executability determination unit determining executability of each of the plurality of generated driving behaviors, a traveling plan selection unit selecting the traveling plan corresponding to the driving behavior with the highest priority, and a traveling control unit controlling the traveling of the host vehicle based on the traveling plan.

A vehicle control device includes a scene determination unit determining whether or not a current traveling scene is a traveling-restricted scene, an order setting unit setting priorities corresponding to a restriction with respect to driving behaviors previously classified for different purposes in a case where it is determined that the traveling scene is the traveling-restricted scene and setting priorities with respect to the plurality of driving behaviors in a case where it is not determined that the traveling scene is the traveling-restricted scene, a traveling plan generating unit generating traveling plans corresponding to the plurality of priority-set driving behaviors, an executability determination unit determining executability of each of the plurality of generated driving behaviors, a traveling plan selection unit selecting the traveling plan corresponding to the driving behavior with the highest priority, and a traveling control unit controlling the traveling of the host vehicle based on the traveling plan.