摘要:
A system and method for dynamically allocating resources in a process. A demand pattern change detection unit, a future demand forecasting unit and a process optimization engine can be employed to constantly adjust resource allocation and assist in maintaining processes in a state of peak performance. An initial resource allocation unit generates an initial resource allocation plan based on past experience with respect to the process. The change detection unit detects a shift in the job demand pattern utilizing a statistical data when a change occurs in process requirements. The future demand generation unit accurately generates future demand data based on current job data and the outlook of future demand. The optimization engine acts as a surrogate process expert and provides recommendations to the process owner regarding potential possible resource allocation policies for new job demand data utilizing a simulation process to predict the result of variable staffing configurations.
摘要:
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.
摘要:
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.
摘要:
A method and system for motivating and optimizing usage of a toll lane by displaying a time based cost metric on an electronic display. The real time electronic display can be configured on the toll lane for displaying information with respect to the toll lane to, for example, a driver on a highway. An average speed of vehicles in the toll lane and/or a non-toll lane of the highway over at least one span can be measured and the average speed can be displayed on the electronic display. A toll rate with respect to the usage of the toll lane can be determined and displayed. A time saving value and a cost per unit time with respect to the usage of the toll lane over the span can be calculated and displayed on the electronic display.
摘要:
A system and method for dynamically allocating resources in a process. A demand pattern change detection unit, a future demand forecasting unit and a process optimization engine can be employed to constantly adjust resource allocation and assist in maintaining processes in a state of peak performance. An initial resource allocation unit generates an initial resource allocation plan based on past experience with respect to the process. The change detection unit detects a shift in the job demand pattern utilizing a statistical data when a change occurs in process requirements. The future demand generation unit accurately generates future demand data based on current job data and the outlook of future demand. The optimization engine acts as a surrogate process expert and provides recommendations to the process owner regarding potential possible resource allocation policies for new job demand data utilizing a simulation process to predict the result of variable staffing configurations.