Abstract: The disclosure generally relates to a system comprising a memory and a processor configured to access the memory and execute the machine-executable instructions stored on the memory to determine that a target vehicle is engaging in an abnormal driving, determine that the abnormal driving exceeds a notification threshold parameter of an abnormal driving notification system, generate a notification, and monitor the ego vehicle and/or driver to alter notification threshold values based on the reactions of the ego vehicle and/or driver inputs.

Abstract: Systems and methods are provided for forming remote vehicular micro clouds at one or more remote locations. According to some embodiments, the methods and systems comprise responsive to receiving a request to form a vehicular micro cloud from a client device, communicating with a plurality of vehicles within an area of a geographic location to collectively form a vehicular micro cloud at the geographic location, where client device is remote from the area of the geographic location. The methods and systems further include receiving resource data from the plurality of vehicles, the resource data comprising detection results of an environment surrounding the geographic location based on sensor sets of the plurality of vehicles, and transmitting the resource data to the client device.

Abstract: An object detection system for a vehicle includes a processor and a memory communicably coupled to the processor. The memory stores instructions that when executed by the processor cause the processor to receive a priority assignment set by an occupant of a vehicle. The priority assignment corresponds to a customization of at least one warning characteristic. The at least one warning characteristic includes a distance threshold. The instructions also cause the processor to detect an object in an external environment of the vehicle and apply the priority assignment to the object. The instructions further cause the processor to issue a warning according to the at least one warning characteristic. According to the distance threshold, the warning is issued when a distance from the vehicle to the object meets the distance threshold.

Abstract: A trailer monitoring system for a vehicle includes a processor and a memory communicably coupled to the processor. The memory stores instructions that when executed by the processor cause the processor to receive, from at least one monocular camera mounted to a vehicle towing a trailer, at least one monocular camera image of at least a portion of the trailer. The instructions also cause the processor to generate at least one depth map based on the at least one monocular camera image. The instructions further cause the processor to identify a trailer irregularity based on the at least one depth map.

Abstract: A parking assist system for a vehicle includes a processor and a memory communicably coupled to the processor. The memory stores instructions that when executed by the processor cause the processor to detect a parking space for a vehicle. The instructions further cause the processor to identify one or more parking parameters related to parking the vehicle in the parking space. The parking parameters include a point-of-interest associated with the parking space. The instructions further cause the processor to determine a suitability of the parking space based on the one or more parking parameters. Determining the suitability of the parking space includes predicting a point-of-interest-related action to be performed by an occupant after parking the vehicle in the parking space.

Abstract: Systems and methods are provided for detecting when a vehicle engages in anomalous driving behavior and managing nearby vehicles to mitigate risk to the nearby vehicles due to the anomalous driving behavior. According to some embodiments, the methods and systems comprise receiving an indication that an anomalous driving behavior of a first vehicle is detected, and identifying a plurality of vehicles within a geographic area of the first vehicle based on receiving the indication. The methods and systems further include generating an arrangement for the plurality of vehicles based on the detected anomalous driving behavior, determining a target speed for each of the plurality of vehicles based on the determined arrangement and a current speed of each of the plurality of vehicles, and communicating control messages to each of the plurality of vehicles. The control messages comprising the target speed to distribute the plurality of vehicles into the determined arrangement.

Abstract: Systems and methods are provided for programmatically verifying an origin of abnormal driving. Some examples of abnormal driving may include aggressive driving (e.g., tailgating, cut-in lane, etc.), distracted driving (e.g., swerving, delayed reaction, etc.), and reckless driving (e.g., green light running, lane change without signaling, etc.). For example, the systems and methods may receive an identification of a second vehicle performing abnormal driving from an ego vehicle; initiate a verification process of the identification of the abnormal driving; access driving data associated with an origin of the abnormal driving, wherein the driving data includes the ego vehicle and the second vehicle; using the driving data, determine a confirm or deny decision regarding the identification of the second vehicle from the ego vehicle; and provide the confirm or deny decision.

Abstract: Systems and methods are provided for forming a knowledge hub. According to some embodiments, the methods and systems comprise determining a region of interest comprising a geographical portion of a roadway, determining an appropriate notification associated with the region of interest, the appropriate notification comprising instructions to navigate the geographical portion of the roadway, examining available resources to generate a knowledge hub about the region of interest and notifying the driver of the vehicle of the appropriate notification associated with the region of interest when the vehicle enters into the region of interest.

Abstract: Systems and methods are provided for forming remote vehicular micro clouds at one or more remote locations. According to some embodiments, the methods and systems comprise responsive to receiving a request to form a vehicular micro cloud from a client device, communicating with a plurality of vehicles within an area of a geographic location to collectively form a vehicular micro cloud at the geographic location, where client device is remote from the area of the geographic location. The methods and systems further include receiving resource data from the plurality of vehicles, the resource data comprising detection results of an environment surrounding the geographic location based on sensor sets of the plurality of vehicles, and transmitting the resource data to the client device.

Abstract: A method of operating a traffic management system may comprise identifying a vehicle queue in a first lane of a road based on sensor data from one or more connected vehicles traveling along the road, determining driving instructions for a connected vehicle within a queue management region in a second lane, adjacent to the first lane, to create a gap in front of the connected vehicle for a vehicle in the vehicle queue to change lanes into the gap, and transmitting the driving instructions to the connected vehicle.

Abstract: The disclosed subject matter relates to managing a vehicular micro cloud. A method may include determining join/leave protocols for a vehicular micro cloud and transmitting the join/leave protocols to a local vehicle in a vicinity of the vehicular micro cloud prior to the local vehicle joining the vehicular micro cloud. The join/leave protocols can define at least: 1) a procedure for the local vehicle to join the vehicular micro cloud and contribute computing resources to a collaborative micro cloud task, and 2) a protocol for handing an incomplete task when the local vehicle leaves the vehicular micro cloud.

Abstract: Compensation can be made for mismatch in abnormal driving behavior detection between an ego vehicle and its human driver. Sensor data of a surrounding driving environment can be acquired. The acquired sensor data can be analyzed to detect abnormal driving behavior by a vehicle in the surrounding driving environment. Responsive to detecting abnormal driving behavior by the vehicle in the surrounding driving environment, the abnormal driving behavior can be classified as to whether it is severe. If the abnormal driving behavior is classified as not being severe, an amplified version of the abnormal driving behavior can be caused to be presented to the human driver of the ego vehicle.

Abstract: System, methods, and other embodiments described herein relate to identifying connected vehicles through invoking maneuvers by vehicles that assist with distinguishing between safety messages having unassociated identifiers originating from the connected vehicles. In one embodiment, a method includes identifying surrounding vehicles including indeterminate vehicles from a driving environment using temporary identifiers received from the surrounding vehicles. The method also includes generating trajectories for the indeterminate vehicles. The method also includes distinguishing the indeterminate vehicles from communications using the temporary identifiers by observing execution of the trajectories by the indeterminate vehicles. The method also includes executing a planning task by a subject vehicle using safety information from the communications.

Abstract: The disclosure includes embodiments for reorganizing autonomous entities to meet a resource demand of a vehicular micro cloud. In some embodiments, a method for a connected vehicle that is a member of the vehicular micro cloud includes modifying an operation of a communication unit of the connected vehicle to receive, via a Vehicle-to-Everything (V2X) network, a reorganization message that includes a reorganization instruction to fulfill the resource demand of the vehicular micro cloud. The method includes executing the reorganization instruction to incorporate one or more resources of an autonomous entity into a resource pool of the vehicular micro cloud so that the resource demand of the vehicular micro cloud is met.

Abstract: Systems include a controller programmed to instruct a sensor to detect an object in an environment of a vehicle in response to an activation of a fall-on-car prevention function, determine a first value of a parameter pertaining to the object at a first time with the sensor, determine a second value of the parameter pertaining to the object at a second time with the sensor, and automatically cause an action to occur based on a comparison of the first value of the parameter and the second value of the parameter.

Abstract: The disclosure includes embodiments for providing altruistic mobility by one or more vehicular micro clouds. The method includes predicting, by a processor, based on sensor data describing a roadway environment that a future conflict of interest between a first set of vehicles and a second set of vehicles will occur in the roadway environment that includes the connected roadway infrastructure device. The method includes forming a first vehicular micro cloud including the first set of vehicles and the connected roadway infrastructure device. The method includes forming a second vehicular micro cloud including the second set of vehicles. The method includes determining steps included in an altruistic action plan that is operable to obviate the future conflict of interest. The method includes instructing the first set of vehicles and the connected roadway infrastructure device to execute the steps of the altruistic action plan to obviate the conflict of interest.

Abstract: The disclosure includes embodiments for predicting an occurrence of a future road hazard in a roadway environment using digital data provided by a vehicular micro cloud. A method according to some embodiments is executed by a processor. In some embodiments, the processor is an element of a vehicle that is itself a member of the vehicular micro cloud. The method includes receiving vehicular micro cloud data describing sensor measurements of a roadway environment and a rule set. The method includes predicting, based on the sensor measurements and the rule set, that a future road hazard will occur. The method includes executing a remedial action plan that obviates the future road hazard. In some embodiments, the remedial action plan is executed by one or more members of the vehicular micro cloud. In some embodiments, digital data describing the prediction and the remedial action plan is broadcast within the roadway environment.

Abstract: Systems and methods for fast vehicular micro cloud formation are disclosed herein. In one example, a system includes a processor and a memory in communication with the processor and having instructions. When executed by the processor, the instructions cause the processor to receive an identifier of the vehicle and determine if the identifier matches the information in stored metadata. If the identifier matches the information in the stored metadata, the vehicle is allowed to join the vehicular micro cloud without performing a standard onboarding procedure. Otherwise, a standard onboarding procedure is performed to allow the vehicle to join the vehicular micro cloud.

Abstract: Systems, methods, and other embodiments described herein relate to improving the identification of available parking spaces by inferring when a vehicle is likely to depart. In one embodiment, a method includes, responsive to acquiring sensor data about a surrounding environment including at least one parked vehicle, extracting a feature from the sensor data about a context of the parked vehicle. The method includes analyzing the feature to determine a status of the vehicle in relation to whether the vehicle is remaining parked. The method includes providing the status to inform additional vehicles about an availability of a parking spot of the parked vehicle.

Abstract: Systems, methods, and vehicles for classifying driving behavior of a target vehicle are provided. The systems include a controller programmed to identify a target vehicle associated with a pseudo-id, obtain a first tag representing first driving behavior of the target vehicle during a first period of time along with the pseudo-id based on first motion data of the target vehicle, obtain a second tag representing second driving behavior of the target vehicle during a second period of time along with the pseudo-id based on second motion data of the target vehicle, the second period of time being after the first period of time, and classify driving behavior of the target vehicle based on interpretation of the first tag and the second tag.