Abstract: A map updating system for a vehicle includes one or more input devices. The input device generates an input signal associated with data indicative of multiple landmark points relative to multiple road semantic features. The system further includes a computer having one or more processors that receive the input signal. The computer further includes a non-transitory computer readable storage medium for storing instructions. The processor is programmed to build a local map including the road semantic features and the landmark points. The processor is further programmed to determine a radius of road curvature associated with each road semantic feature and compare the radius of road curvature to a maximum radius of curvature threshold. The processor is further programmed to transmit an update signal to a cloud server, in response the processor determining that the radius of road curvature is less than the maximum radius of curvature threshold.

Abstract: A method to schedule intelligent traffic lights in real time based on digital infochemicals (DIs) is disclosed. The method takes advantage of DIs as medium to both predicate traffic flow and smooth the green/Cycle (g/C) ratio. First collect DIs, then update DIs by three actions including aggregation, evaporation, and propagation. After that, adjust the g/C ratio of the traffic light. DIs have the function of prediction due to the propagation that allows DIs reach the traffic earlier than the real traffic flow. On the other hand, DIs have the function of memory due to the evaporation that remembers the information of the historical traffic flow. The prediction and memory of DIs, as the reason why DIs are superior to the pure traffic flow, give the DI-based intelligent traffic light compelling advantages over the pure traffic based intelligent traffic light.

Abstract: A method to schedule intelligent traffic lights in real time based on digital infochemicals (DIs) is disclosed. The method takes advantage of DIs as medium to both predicate traffic flow and smooth the green/Cycle (g/C) ratio. First collect DIs, then update DIs by three actions including aggregation, evaporation, and propagation. After that, adjust the g/C ratio of the traffic light. DIs have the function of prediction due to the propagation that allows DIs reach the traffic earlier than the real traffic flow. On the other hand, DIs have the function of memory due to the evaporation that remembers the information of the historical traffic flow. The prediction and memory of DIs, as the reason why DIs are superior to the pure traffic flow, give the DI-based intelligent traffic light compelling advantages over the pure traffic based intelligent traffic light.

Abstract: A method and system for providing a feedback based dynamic pricing algorithm with an embedded controller for a HOT (High Occupancy Toll) lane. An input-output transfer function of a vehicle flow with respect to a HOT lane can be obtained utilizing a simulation module. A feedback controller combined with, for example, a Smith predictor can be designed to avoid an unstable behavior due to a time delay in the HOT lane, a price regulation, and a large transient caused by an integral part of the controller due to traffic jams. A driver behavior preference model can be derived based on a relationship between a toll rate and several characteristics of the HOT lane and a general purpose lane. The feedback controller and the behavior preference model can then be implemented to set the toll rate in real-time in order to satisfy a desired performance metric.

Abstract: The disclosed embodiments illustrate methods and systems for determining strategies in crowdsourcing. The method includes generating first graphs representative of an association between workers, between crowdsourcing tasks, or between workers and crowdsourcing tasks, at first time instance. The method includes determining values of metrics associated with first graphs, comparing determined values of metrics and threshold values of metrics, and generating second graphs based on comparison. The second graphs are representative of an association between workers, between crowdsourcing tasks, or between workers and crowdsourcing tasks, at second time instance. The second time instance precedes first time instance. Thereafter, the method includes determining strategies based on second graphs. The strategies comprise recommendation to a first set of workers for attempting a first set of crowdsourcing tasks or recommendation to first set of workers for increasing interaction with second set of workers.

Abstract: The disclosed embodiments illustrate methods and systems for recommending crowdsourcing tasks. A first crowdsourcing task is received from a requestor. Based on the first crowdsourcing tasks a set of second crowdsourcing tasks, previously attempted by one or more crowdworkers is determined. The set of second crowdsourcing tasks is determined based on a degree of similarity between the first crowdsourcing task and each of the one or more sets of second crowdsourcing tasks. Further, the first crowdsourcing task is recommended to a set of crowdworkers from the one or more crowdworkers based on performance of the set of crowdworkers on the set of second crowdsourcing tasks.

Abstract: Methods and systems for creating statistical model. Values of at least one output parameter corresponding to each combination of values of a set of input parameters are collected. The at least one output parameter and the set of input parameters are associated with one or more crowdsourcing tasks. Each combination of the values of the set of input parameters is determined based on at least one of one or more design of experiments or a historical data. Further, a distribution of the values of the at least one output parameter is determined. The statistical model is created based on the values of the set of input parameters and one or more characteristics associated with the distribution of the values of the at least one output parameter.

Abstract: According to embodiments illustrated herein, there is provided a method for recommending one or more first tasks to one or more workers. The method includes determining a first score for a count of transactions, a second score for each of one or more locations based on a result of one or more second tasks in each of the one or more locations, and a third score for each of one or more industries based on a result of the one or more second tasks in each of the one or more industries. The method further includes ranking the one or more first tasks based on at least the first score, the second score, the third score, and one or more attributes associated with the one or more first tasks. Thereafter, the ranked one or more first tasks are presented to the one or more workers.

Abstract: Methods, systems and processor-readable media for modeling and optimizing multiple ITS (Intelligent Transportation System) strategies utilizing a systematic genetic algorithm. A traffic simulation model can be configured in conjunction with a genetic algorithm based optimization engine for optimizing the transportation models. An origin-destination matrix that minimizes discrepancies between a simulated and an observed link traffic count can be estimated by considering a road network and a traffic count with respect to a region. A driver behavior can then be determined utilizing the origin-destination matrix via calibration so that the simulation model can replicate a freeway traffic flow in the region. An optimal parameter with respect to the ITS strategies can be determined to optimize a set goal with respect to a given constraint. Such an approach meets a level of service (LOS) metric as well as a revenue target under the applied ITS strategies.

Abstract: Methods and systems for creating statistical model. Values of at least one output parameter corresponding to each combination of values of a set of input parameters are collected. The at least one output parameter and the set of input parameters are associated with one or more crowdsourcing tasks. Each combination of the values of the set of input parameters is determined based on at least one of one or more design of experiments or a historical data. Further, a distribution of the values of the at least one output parameter is determined. The statistical model is created based on the values of the set of input parameters and one or more characteristics associated with the distribution of the values of the at least one output parameter.

Abstract: An apparatus and method of predicting the end of life of a consumable. A basic weighted least squares algorithm has been extended and augmented to compensate for observed common consumable/printer behavior. The system uses consumable usage data (such as toner level) acquired from the device to predict the current and future consumable level and to predict the remaining life. The apparatus and method monitors the consumable's usage and updates the prediction so that when the predicted remaining life matches a preset threshold, it automatically triggers an order placement event to ship product to customer.

Abstract: The disclosed embodiments illustrate methods and systems for creating a simulator for a crowdsourcing platform. The method includes generating a plurality of rules indicative of at least one of a behavior or an interaction, of one or more entities associated with the crowdsourcing platform, based on one or more parameters associated with each of the one or more entities. Thereafter, a first level of service of the crowdsourcing platform is estimated based on the generated plurality of rules. Further, the plurality of rules are modified based on the first level of service and an observed level of service of the crowdsourcing platform. The plurality of rules are modified such that a second level of service of the crowdsourcing platform, estimated based on the modified plurality of rules, approaches the observed level of service of the crowdsourcing platform. The modified plurality of rules corresponds to the simulator for the crowdsourcing platform.

Abstract: Methods and systems for dynamic pricing based on sliding mode control with respect to a HOT (High Occupancy Toll) lane. The controller consists of a feed-forward path and a feedback path. In the feed-forward path, a sliding mode controller in association with a sliding mode control module can be configured to achieve desired performance objectives under time-varying system parameters in real-time. An estimated VOT (Value of Time) distribution can be derived in association with the controller to reduce the difference between an actual and target traffic flow density on the HOT lane. The estimation of the VOT distribution can be updated by the controller at each time interval when the difference in densities is larger than a certain threshold. A low pass filter can also be employed to substantially improve prediction and the calculation of tolls to reduce fluctuations in traffic.

Abstract: An apparatus and method of predicting the end of life of a consumable. A basic weighted least squares algorithm has been extended and augmented to compensate for observed common consumable/printer behavior. The system uses consumable usage data (such as toner level) acquired from the device to predict the current and future consumable level and to predict the remaining life. The apparatus and method monitors the consumable's usage and updates the prediction so that when the predicted remaining life matches a preset threshold, it automatically triggers an order placement event to ship product to customer.

Abstract: Method and system for dynamically adjusting compensation for one or more tasks are disclosed. The method includes estimating the compensation for each task in a batch of tasks based on at least one of a minimum wage for a task in the batch of tasks, one or more attributes associated with the worker, a number and type of tasks in the batch of tasks, or a target level of service. The compensation for the each task of the batch of tasks is then adjusted based on at least one of an observed level of service associated with the batch of tasks and the target level of service. The method is performed using a processor.

Abstract: Methods, systems and processor-readable media for modeling and optimizing multiple ITS (Intelligent Transportation System) strategies utilizing a systematic genetic algorithm. A traffic simulation model can be configured in conjunction with a genetic algorithm based optimization engine for optimizing the transportation models. An origin-destination matrix that minimizes discrepancies between a simulated and an observed link traffic count can be estimated by considering a road network and a traffic count with respect to a region. A driver behavior can then be determined utilizing the origin-destination matrix via calibration so that the simulation model can replicate a freeway traffic flow in the region. An optimal parameter with respect to the ITS strategies can be determined to optimize a set goal with respect to a given constraint. Such an approach meets a level of service (LOS) metric as well as a revenue target under the applied ITS strategies.

Abstract: A point-based method, system and processor-readable medium for reducing traffic congestion. A license plate number associated with a vehicle can be captured utilizing an image capturing unit and/or a GPS (Global Positioning System) enabled mobile communication device to store/deduct points with respect to a user account on a point storage server. The points can be stored in a user account based on a dynamic policy if a user selects a sub-optimal path (e.g., general-purpose lane or a far-away parking spot) and the level of urgency related to travel is low to reduce congestion. The points can be deducted later if the user decides to take an optimal path (e.g., HOT lane or a near-center parking spot). The points on each path can be dynamically set based on time of day to maintain traffic flow at an optimal level.

Abstract: A method and system for providing a feedback based dynamic pricing algorithm with an embedded controller for a HOT (High Occupancy Toll) lane. An input-output transfer function of a vehicle flow with respect to a HOT lane can be obtained utilizing a simulation module. A feedback controller combined with, for example, a Smith predictor can be designed to avoid an unstable behavior due to a time delay in the HOT lane, a price regulation, and a large transient caused by an integral part of the controller due to traffic jams. A driver behavior preference model can be derived based on a relationship between a toll rate and several characteristics of the HOT lane and a general purpose lane. The feedback controller and the behavior preference model can then be implemented to set the toll rate in real-time in order to satisfy a desired performance metric.