Abstract: Systems and methods are provided for improving the performance of anomaly detection, including detecting abnormal driving behavior at locations and in driving situations where the accuracy of detecting abnormal driving behavior has decreased or known to cause inaccurate performance responses. For example, the anomaly detection mechanism may detect abnormal driving behavior (e.g., delayed responses, road rage, swerving, etc.) or environmental anomalies (e.g., potholes, fallen trees, etc.), and particular driving situations or locations can have repeatedly shown decreased rates of accuracy with responding to these anomalies, including abnormal driving behavior (e.g., delayed driver responses to left-turns, U-turns, traffic light, railroad crossing, construction zones, etc.) or situations that are known to cause inaccurate performance responses (e.g., potholes, fallen trees, etc.). Embodiments can revise the anomaly detection system to operate the vehicle more consistently with other human drivers.

Abstract: The disclosure describes a method for an ego vehicle. The method includes determining that a vehicle needs to park. The method further includes identifying a parking facility within proximity to the vehicle and a corresponding congestion level of the parking facility. The method further includes selecting a first parking model from two or more parking models based on the corresponding congestion level being closer to a first congestion range than a second congestion range. The method further includes identifying a parking spot for the vehicle within the parking facility based on the first parking model.

Abstract: A system for communicating a traffic condition to an upstream vehicle can include a processor, disposed on an ego vehicle, and a memory. The memory can store a determination module and a communications module. The determination module can include instructions that cause the processor to determine, by the ego vehicle in a first lane, an existence of the traffic condition that includes a difference, between an actual velocity of a vehicle in a second lane and an expected velocity, being greater than a threshold. The communications module can include instructions that cause the processor to: (1) cause, in response to the existence, a communications device of the ego vehicle to communicate, to the upstream vehicle, information about the traffic condition and (2) cause, in response to an absence of the existence, the communications device to refrain from communicating, to the upstream vehicle, the information about the traffic condition.

Abstract: An embodiment of the present invention is an information processing system including: a user terminal carried by a user; and an information processing device being able to communicate with the user terminal. The information processing device has: a storage storing product information of a product to be reduced in price in a store, condition information showing a condition of the product, and offered price information of the product, in association with one another; and a payment processor configured to perform a payment process of the product based on a payment request of the product corresponding to the product information acquired from the user terminal. The user terminal has a display controller that acquires the condition information and the offered price information corresponding to the product information of the product selected by the user, from the information processing device, and to cause a display to show the acquired information.

Abstract: Systems and methods of unsafe driving detection are provided which share partial unsafe driving behavior analyses with others in order to ensure that unsafe driving behavior is detected as early as possible. For example, in response to an event which interrupts a first detecting vehicle from collecting additional driving behavior data associated with a subject vehicle, the first detecting vehicle may transfer driving behavior data it has already collected and processed, to another detecting entity (e.g., a second detecting vehicle) in observable range of the subject vehicle.

Abstract: In an example, a method determines a first controllable vehicle traveling along a mitigation road segment of a roadway and determines a control lane in the mitigation road segment. The control lane includes the first controllable vehicle and is impedible by the first controllable vehicle. The method determines a first open lane in the mitigation road segment and applies a target mitigation speed to the first controllable vehicle in the control lane. The first open lane is adjacent to the control lane in the mitigation road segment and the target mitigation speed is based on a traffic state of the first open lane. The target mitigation speed adjusts a traffic stream that flows through the first open lane to mitigate traffic congestion located downstream of the mitigation road segment.

Abstract: System, methods, and other embodiments described herein relate to improving identification of available parking spaces in congested zones. In one embodiment, a method includes, responsive to receiving trajectory information about movement of a searching vehicle, estimating a search time spent by the vehicle seeking parking in a location. The method includes aggregating, when the search time satisfies a time threshold, the search time with observed times associated with additional entities parking in the location. The method includes updating a parking map according to the observed times when the observed times satisfy a parking threshold indicating a lack of available parking in the location. The parking map identifies active regions where parking is presently lacking. The method includes providing the parking map with the active regions to identified vehicles proximate to locations associated with the active regions.

Abstract: An embodiment of an information processing system includes a user terminal carried by a user; and a server being capable of communicating with the user terminal. The user terminal is comprised of: an obtaining unit configured to obtain product information and expiration information related to an expiration date of a product from the product; and a display controller configured to cause a display to show information containing an offered price of the product, which is acquired from the server. The server is comprised of: a price determination unit configured to determine the offered price of the product based on the product information and the expiration information acquired from the user terminal; and a price information providing unit configured to provide information that contains the offered price of the product determined by the price determination unit, to the user terminal.

Abstract: A method comprises receiving a service request from a vehicle, obtaining environment data with one or more sensors, determining a vehicle type of the vehicle based on the service request, determining service data responsive to the service request based on the vehicle type of the vehicle and the environment data, and transmitting a service message comprising the service data to the vehicle.

Abstract: A system for providing information to navigate to a parking space preferred by an operator of a vehicle can include a processor and a memory. The memory can store a preliminary operations module and a communications module. The preliminary operations module can include instructions that cause the processor to obtain, for the operator: (1) a first model for a first duration between a commencement of a parking space identification process and a first threshold and (2) a second model for a second duration between the first threshold and a second threshold. The communications module can include instructions that cause the processor to communicate, to a component of the vehicle for an action, information to navigate to the parking space. The parking space can be identified, in response to a current time being within: (1) the first duration, by the first model and (2) the second duration, by the second model.

Abstract: A system for monitoring a traffic condition can include a processor and a memory. The memory can store a preliminary operations module, a calculations module, and a communications module. The preliminary operations module can include instructions that cause the processor to obtain information about the traffic condition of stopped or slow moving vehicles. The calculations module can include instructions that cause the processor to: (1) define a monitoring zone that encloses the traffic condition and (2) determine, based on data about velocities of vehicles in the monitoring zone, that an error of a prediction of a position of a vehicle, associated with the traffic condition, is less than a threshold. The communications module can include instructions that cause the processor to: (1) receive the data and (2) cause, in response to a determination that the error is less than the threshold, the information to be communicated to vehicles.

Abstract: A system for communicating a traffic condition to an upstream vehicle can include a processor, disposed on an ego vehicle, and a memory. The memory can store a determination module and a communications module. The determination module can include instructions that cause the processor to determine, by the ego vehicle in a first lane, an existence of the traffic condition that includes a difference, between an actual velocity of a vehicle in a second lane and an expected velocity, being greater than a threshold. The communications module can include instructions that cause the processor to: (1) cause, in response to the existence, a communications device of the ego vehicle to communicate, to the upstream vehicle, information about the traffic condition and (2) cause, in response to an absence of the existence, the communications device to refrain from communicating, to the upstream vehicle, the information about the traffic condition.

Abstract: Systems and methods described herein relate to coordinated vehicle lane assignment. One embodiment receives from a locality manager, at a section manager that communicates with one or more connected vehicles in a section of a roadway, target lateral flows for two or more lanes of the roadway in the section of the roadway; converts the target lateral flows to a target number of connected vehicles N at the section manager; selects for lane change, at the section manager, a set of N connected vehicles whose ranked distances from a following vehicle in a target lane are greatest among the one or more connected vehicles, when a direction of lane change is uniform among the set of N connected vehicles; and transmits lane-change actions from the section manager to the set of N connected vehicles.

Abstract: Systems and methods described herein relate to coordinated vehicle lane assignment using reinforcement learning. One embodiment receives from a locality manager, at a section manager that communicates with a plurality of connected vehicles in a section of a roadway, target lateral flows for two or more lanes of the roadway in the section of the roadway; receives, at the section manager, traffic state information from the plurality of connected vehicles; processes, at the section manager, the traffic state information and the target lateral flows using a reinforcement-learning-based model to determine lane-change actions for the plurality of connected vehicles, wherein the reinforcement-learning-based model is based on a single neural network with shared parameters for the plurality of connected vehicles; and transmits the lane-change actions from the section manager to the plurality of connected vehicles.

Abstract: Systems and methods described herein relate to traffic-flow regulation via centralized lateral flow control. One embodiment receives, at a locality manager that regulates traffic flow on a roadway via lateral flow control, aggregated macroscopic traffic state information from a section manager that communicates with one or more connected vehicles in a section of the roadway; processes the aggregated macroscopic traffic state information at the locality manager using a reinforcement-learning-based model to determine target lateral flows for two or more lanes of the roadway in the section of the roadway; and transmits the target lateral flows from the locality manager to the section manager, which converts the target lateral flows to lane-change actions and transmits the lane-change actions to the one or more connected vehicles.

Abstract: A method for generating a dataset is provided. The method includes generating, within a simulated environment, a simulated image including one or more distortions, the simulated image includes a plurality of vehicles, generating vehicle image patches and ground truth from the simulated image, performing, using a style transfer module, a style-transfer operation on the vehicle image patches, combining the vehicle image patches, on which the style-transfer operation is performed, with a background image of a real-world location, and generating a dataset based on the ground truth and the combination of the vehicle image patches and the background image.

Abstract: A method for automatically learning parking preferences for a driver and generating parking recommendations includes generating training data based at least in part on: 1) trajectory data indicating a trajectory of a vehicle during a plurality of parking events, each in which a driver of the vehicle selected a parking candidate from among a plurality of parking candidates, and 2) attribute data indicating attributes of each of the plurality of parking candidates, removing, from the training data, data associated with at least one available parking candidate based on one or more conditions that indicate the driver did not consider the at least one available parking candidate, and training a decision model, based on remaining training data, to estimate a preferred parking candidate for the driver from among a set of available parking candidates.

Abstract: In accordance with one embodiment of the present disclosure, method includes obtaining multi-level environment data corresponding to a plurality of driving environment levels, encoding the multi-level environment data at each level, extracting features from the multi-level environment data at each encoded level, fusing the extracted features from each encoded level with a spatial-temporal attention framework to generate a fused information embedding, and decoding the fused information embedding to predict driving environment information at one or more driving environment levels.

Abstract: A system for managing vehicles includes a plurality of first level managers, and a plurality of second level managers each being in a higher hierarchical level than the plurality of first level managers and managing a section. Each of the plurality of first level managers collects data using one or more sensors of a vehicle, abstracts the data to obtain first information, and transmits a first instruction to the vehicle based on the first information. One of the plurality of second level managers receives the first information from one or more of the plurality of first level managers in the section managed by the one of the plurality of second level managers, obtains second information based on the first information, and transmits a second instruction to the vehicle based on the second information. The first instruction is different from the second instruction.

Abstract: System, methods, and other embodiments described herein relate to predicting trajectories of multiple vehicles using graphs and multiple decoding models. In one embodiment, a method includes computing, using an encoding model, a graph having a geographic map and vehicle features associated with a plurality of vehicles in an area according to characteristics, prior trajectories, and spatiotemporal interactions. The method also includes processing, using the encoding model, updates for the geographic map and the vehicle features separately in association with encoded features of neighboring vehicles. The method also includes decoding, using a probability model and a regression model, the geographic map and the vehicle features to output estimated trajectories for the plurality of vehicles.