Abstract: A method and system for calculating route guidance for a personal transport device based on prosocial costs is described. In one embodiment, the method includes calculating, by a processor associated with the personal transport device, a plurality of routes from a first location to a second location and determining, by the processor, one or more prosocial factors associated with each route of the plurality of routes. The method also includes calculating, by the processor, a prosocial cost associated with each route of the plurality of routes. Based on the prosocial costs, the method further includes providing, by the processor, route guidance to a user of the personal transport device from the first location to the second location along a selected route from the plurality of routes and displaying the selected route on a display associated with the personal transport device.

Abstract: A method and system for implementing real-time feedback to a user of a personal transport device, such as an electric scooter, based on prosocial behavior is provided. In one embodiment, the method includes detecting at least one object located on a path on which the personal transport device is traveling and calculating a prosocial yielding behavior parameter associated with the at least one object and the personal transport device. The method also includes comparing the calculated prosocial yielding behavior parameter to a threshold value and, based on the comparison of the calculated prosocial yielding behavior parameter to the threshold value, providing real-time feedback to the user of the personal transport device.

Abstract: A method and system for modifying range of a battery of a personal transport device based on prosocial behavior is described. In one embodiment, the method includes detecting at least one object located on a path on which the personal transport device is traveling and calculating a prosocial yielding behavior parameter associated with the at least one object and the personal transport device. The method also includes comparing the calculated prosocial yielding behavior parameter to a threshold value. Based on the comparison of the calculated prosocial yielding behavior parameter to the threshold value, access is provided to at least a part of a power reserve portion of a battery of the personal transport device.

Abstract: An automated vehicle (AV) is configured to perform automated travel, and includes vehicle sensors configured to detect a second vehicle in a surrounding environment of the AV. The AV includes at least one of a brake mechanism, an accelerator mechanism, a steering control, and a user interface configured to generate a user response to automated travel by the AV. The AV includes a computing device configured to identify an interaction between the AV and the second vehicle while executing an automated travel path, and receive user responses to automated travel by the AV. The computing device is configured to determine at least one aspect of wellbeing, trust, and satisfaction of the user riding the AV based on the user responses, and determine a learned optimal policy which increases the at least one aspect of wellbeing, trust, and satisfaction based on the user responses.

Abstract: According to one aspect, a system for trust calibration may include a processor and a memory. The memory may store one or more instructions. The processor may execute one or more of the instructions stored on the memory to perform one or more acts, actions, or steps, such as receiving a record of one or more interactions between a user and a first autonomous device, building a trust profile for the user based on one or more of the interactions between the user and the first autonomous device, and operating a target autonomous device based on the trust profile.

Abstract: Systems and methods for determining trust across mobility platforms are provided. In one embodiment, a method includes receiving first mobility data for a first automation experience of a user with a first mobility platform. The method also includes receiving a swap indication for a second automation experience of the user with a second mobility platform after the first automation experience. The method further includes selectively assigning the first mobility platform to a first mobility category and the second mobility platform to a second mobility category different than the first mobility category. The method yet further includes calculating an estimated trust score for the second automation experience by applying a trust model based on the first mobility category, the second mobility category, and a sequence of the first automation experience and the second automation experience. The method includes modifying operation of the second mobility platform based on the estimated trust score.