Abstract: Methods, systems, and apparatuses to build an explainable user output to receive input feature data by a neural network of multiple layers of an original classifier; determine a semantic function to label data samples with semantic categories; determine a semantic accuracy for each layer of the original classifier within the neural network; compare each layer based on results from the comparison of the semantic accuracy; designate a layer based on an amount of computed semantic accuracy; extend the designated layer by a category branch to the neural network to extract semantic data samples from the semantic content to train a set of new connections of an explainable classifier to compute a set of output explanations with an accuracy measure associated each output explanation for each semantic category of the plurality of semantic categories, and compare the accuracy measure for each output explanation to generate the output explanation in a user understandable format.

Abstract: A system for operating a personal energy consumption account for a user includes a mobile application adapted to interface with the user and provide access to the personal energy consumption account. A controller is in communication with the mobile application. The controller is configured to obtain respective activity data of the user in a plurality of domains. The controller is configured to calculate respective carbon dioxide emissions for the plurality of domains. The plurality of domains is grouped into one or more energy clusters each defining a respective range of carbon dioxide emissions. The controller is configured to determine a respective score for the one or more energy clusters based in part on the respective carbon dioxide emissions, a respective average population consumption value and a respective energy budget. The controller is configured to generate recommendations for the user to improve the respective score.

Abstract: A system and method for operating an automated vehicle. A sensor is configured to monitor an ORU (other road user) external to the automated vehicle thereby identifying the ORU with respect to the automated vehicle. A processor determines a state of the ORU and a context of the ORU and communicates a message to the ORU based on the determined state of the ORU and the context of the ORU.

Abstract: Systems and methods are provided for controlling a vehicle. In one embodiment, a method includes: storing, in a data storage device, a decision model, wherein the decision model predicts when to automatically perform a motivational lane change; updating, by a processor, the decision model based on data obtained in response to user input; and automatically requesting, by the processor, a lane change based on the dynamically updated model.

Abstract: A system for notifying a user of a vehicle includes a receiving module configured to receive detection data, and a threat analysis module configured to receive object detection data related to a detected object in an environment around the vehicle, acquiring a predicted trajectory of the detected object, and determine whether the detected object constitutes a threat based on the predicted trajectory of the detected object and a vehicle trajectory. The system also includes a threat display module configured to determine an operating scenario based on a user attentiveness, a field of view, an operating mode, and a threat level, and generate a notification to the user representing the threat, the notification including a visual representation of the detected object and a visual indicator of the predicted trajectory of the detected object. At least one of the visual representation and the visual indicator is customized based on the operating scenario.

Abstract: A controller is provided to predict potential future engagement or disengagement of an automated driving feature in a vehicle and proactively implement operations to reduce the likelihood of the disengagement or increase the likelihood of the engagement.

Abstract: Systems and method are provided for controlling a vehicle having one or more batteries. In one embodiment, a method includes: receiving, by a processor, data from at least two of a user of the vehicle, the vehicle, one or more charging stations, and one or more vehicle services; determining, by the processor, optimization criteria based on the received data; computing, by the processor, a charging route solution based on the optimization criteria; and generating, by the processor, interface data for presenting the charging route solution to the user of the vehicle.

Abstract: Methods, systems, and apparatuses to build an explainable user output to receive input feature data by a neural network of multiple layers of an original classifier; determine a semantic function to label data samples with semantic categories; determine a semantic accuracy for each layer of the original classifier within the neural network; compare each layer based on results from the comparison of the semantic accuracy; designate a layer based on an amount of computed semantic accuracy; extend the designated layer by a category branch to the neural network to extract semantic data samples from the semantic content to train a set of new connections of an explainable classifier to compute a set of output explanations with an accuracy measure associated each output explanation for each semantic category of the plurality of semantic categories, and compare the accuracy measure for each output explanation to generate the output explanation in a user understandable format.

Abstract: A system and method for operating an automated vehicle. A sensor is configured to monitor an ORU (other road user) external to the automated vehicle thereby identifying the ORU with respect to the automated vehicle. A processor determines a state of the ORU and a context of the ORU and communicates a message to the ORU based on the determined state of the ORU and the context of the ORU.

Abstract: Systems and methods are provided for controlling a vehicle. In one embodiment, a method includes: storing, in a data storage device, a decision model, wherein the decision model predicts when to automatically perform a motivational lane change; updating, by a processor, the decision model based on data obtained in response to user input; and automatically requesting, by the processor, a lane change based on the dynamically updated model.

Abstract: Systems and methods are provided for controlling a vehicle. In one embodiment, a method includes: storing, in a data storage device associated with the vehicle, data defining a plurality of modes, wherein the data includes for each mode of the plurality of modes a mode type, at least one vehicle maneuver, and control parameters associated with the at least one vehicle maneuver; dynamically updating, by a processor, at least one of the mode type, the at least one vehicle maneuver, and the control parameters for at least one of the plurality of modes based on user input; and controlling the vehicle based on the dynamically updated mode.

Abstract: A controller is provided to predict potential future engagement or disengagement of an automated driving feature in a vehicle and proactively implement operations to reduce the likelihood of the disengagement or increase the likelihood of the engagement.

Abstract: A system and method obtain a cruise speed for a vehicle. The method includes computing an optimal speed for the vehicle in consideration of traffic flow, the computing the optimal speed being based on the cruise speed and additional information. The method also includes determining a personalized speed for the vehicle based on a model corresponding with a current user of the vehicle, and suggesting the personalized speed to the current user for a response. A new cruise speed for the vehicle is set according to the response of the current user. The vehicle is controlled to travel at the new cruise speed.

Abstract: A method of alerting a user includes storing data regarding a plurality of inputs via a controller having a memory and a processor, and determining if a predetermined threshold is reached in light of the inputs. The method also includes activating an indicator of a seat when the predetermined threshold is reached to alert the user. An alert system includes a seat. The seat includes an indicator. The alert system also includes a controller in communication with the indicator. The controller includes a processor and a memory having recorded instructions for alerting a user. The controller is configured to store data regarding a plurality of inputs and determine if a predetermined threshold is reached in light of the inputs. The controller is also configured to activate an indicator of a seat when the predetermined threshold is reached to alert the user.

Abstract: A mobility planning server is disclosed that is configured to: receive a listing of one or more scheduled activities for a plurality of users; identify a plurality of different types of mobility modes potentially available to transport the users; retrieve, from one or more service providers of the mobility modes, the potential availability of the mobility modes provided by the service provider and any service provider indicated constraints regarding the mobility modes; analyze the one or more scheduled activities, identified mobility modes, the potential availability of the mobility modes, and constraints indicated by any service provider; prepare a mobility plan for each user based on the analysis wherein the mobility plans include a mobility planning server selected mobility mode for each activity; confirm the availability of mobility modes included in the mobility plans; confirm user acceptance of the mobility plans; and schedule a selected mobility mode for each activity.

Abstract: A method of operating a transportation service includes calculating a trip route for a trip request from a commuter, and transmitting a pick-up instruction to a transporting vehicle. A ride rebate option is communicated to the commuter, who may opt to execute it. The ride rebate option may include an option to purchase goods from a third-party provider, provide data to the third-party provider, complete a survey, or promote the third-party provider on social media. The third-party provider is notified when the commuter opts to execute the ride rebate option. Upon confirmation by the third-party provider that the commuter has executed the ride rebate option, a payment amount is transferred from the third-party provider to the transportation service. A fee charged to the commuter by the transportation service is reduced by the payment amount transferred to the transportation service from the third-party provider.

Abstract: A user-centric driving-support system for implementation at a vehicle of transportation. The system in various embodiments includes one or more vehicle sensors, such as a camera, a RADAR, and a LiDAR, and a hardware-based processing unit. The system further includes a non-transitory computer-readable storage device including an activity unit and an output-structuring unit. The activity unit, when executed by the hardware-based processing unit, determines, based on contextual input information, at least one of an alert-assessment output and a scene-awareness output, wherein the contextual input information includes output of the vehicle sensor. The output-structuring unit, when executed by the hardware-based processing unit, determines an action to be performed at the vehicle based on at least one of the alert-assessment output and the scene-awareness output determined by the activity unit.

Abstract: Examples of techniques for controlling a volume of an audio device or system based on a user profile are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes generating, by a processing device, a user volume profile. The method further includes receiving, by the processing device, a volume command to change a volume level of audio. The method further includes determining, by the processing device, a volume change factor based at least in part on the user volume profile. The method further includes changing, by the processing system, the volume level of the audio based at least in part on the volume change factor.

Abstract: Examples of techniques for controlling a volume of an audio device or system based on a user profile are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes generating, by a processing device, a user volume profile. The method further includes receiving, by the processing device, a volume command to change a volume level of audio. The method further includes determining, by the processing device, a volume change factor based at least in part on the user volume profile. The method further includes changing, by the processing system, the volume level of the audio based at least in part on the volume change factor.

Abstract: Systems and method are provided for issuing a driver alert. In one embodiment, a method includes: receiving, via a processor, driving parameter data representing a current driving parameter for a driving vehicle, receiving, via the processor, threshold data representing driving thresholds for the at least one driving parameter, determining, via the processor, whether to issue a driver alert based on the threshold data and the driving parameter data, thereby producing alert data, and generating and outputting an in-vehicle driver alert based on the alert data.