DYNAMIC PRICING BASED ON SLIDING MODE CONTROL AND ESTIMATION FOR HIGH OCCUPANCY TOLL LANES

• US 20150106171A1
• Filed: 10/11/2013
• Published: 04/16/2015
• Est. Priority Date: 10/11/2013
• Status: Abandoned Application

• Current Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Zou, Guangyu, Fu, Lina, Kulkarni, Rakesh S.
• Application Number:
  US14/051,927
• Publication Number:
  US 20150106171A1
• Time in Patent Office: Days
• US Class Current: 705/13
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

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.

Claims

1. A sliding mode based dynamic pricing method for a high occupancy toll lane, said method comprising:

determining an optimal target traffic flow density with respect to at least one high occupancy toll lane to achieve one or more desired performance objectives;

designing a pricing controller that includes a feed-forward path and a feedback path, wherein said feed-forward path is configured with a sliding mode controller in association with a sliding mode control module to update in real-time an estimated value of time of drivers;

configuring said sliding mode controller to update said estimated value of time to reduce a difference between an actual traffic flow density and the said target traffic flow density with respect to said at least one high occupancy toll lane, such that said estimated value of time is updated at each time interval when said difference in said actual traffic flow density and said target traffic flow density is larger than a particular threshold;

generating a base toll price from said feed-forward path based on said estimated value of time, a driver decision model and an estimated potential traffic demand so that an estimated number of vehicles entering said at least one high occupancy toll lane in a next time interval will match said target traffic flow density;

generating an adjustment toll price from said feedback path based on said difference between said actual traffic flow density and said target traffic flow density with respect to said at least one high occupancy toll lane to reduce said difference, wherein said base toll price and said adjustment toll price are combined to produce a final toll price.

2. The method of claim 1 further comprising configuring a low pass filter in said sliding mode controller to obtain a smoother estimation of value of time and to reduce fluctuation in traffic with respect to said at least one high occupancy toll lane.

3. The method of claim 2 further comprising:

selecting a sliding surface and a discontinuous input to change said estimated value of time to drive dynamics of said controller towards said sliding surface wherein said sliding surface represents a desired system state.

5. The method of claim 1 further comprising using said estimated value of time to provide information for a study of time-varying driver choice behavior in terms of a distribution associated with said estimated value of time.

6. The method of claim 1 further comprising:

determining a driver decision model wherein a driver decides to enter said at least one high occupancy toll lane by a utility function with respect to said at least one high occupancy toll lane and at least one general purpose lane respectively based on said estimated value of time and said toll price;

selecting said at least one high occupancy toll lane by said driver if a ratio of said utility function for said at least one high occupancy toll lane to said utility function for said at least one general purpose lane is greater than a particular threshold.

7. The method of claim 3 further comprising:

obtaining an average value of time distribution signal by said low pass filter; and

updating an estimate of said average value of time distribution signal at each time interval; and

utilizing said estimate of said average value of time distribution signal to determine said base toll price in order to drive said sliding surface towards zero.

8. The method of claim 7 further comprising configuring said average value of time distribution signal in association with sliding mode feedback to further reduce oscillation.

4. The method of claim 4 further comprising permitting said discontinuous input to increase or decrease said estimated value of time upon a deviation from said sliding surface.

9. A sliding mode based dynamic pricing system for a high occupancy toll lane, said system comprising:

a processor; and

a computer-usable medium embodying computer program code, said computer-usable medium capable of communicating with the processor, said computer program code comprising instructions executable by said processor and configured for;

determining an optimal target traffic flow density with respect to at least one high occupancy toll lane to achieve one or more desired performance objectives;

designing a pricing controller that includes a feed-forward path and a feedback path, wherein said feed-forward path is configured with a sliding mode controller in association with a sliding mode control module to update in real-time an estimated value of time of drivers;

configuring said sliding mode controller to update said estimated value of time to reduce a difference between an actual traffic flow density and the said target traffic flow density with respect to said at least one high occupancy toll lane, such that said estimated value of time is updated at each time interval when said difference in said actual traffic flow density and said target traffic flow density is larger than a particular threshold;

generating a base toll price from said feed-forward path based on said estimated value of time, a driver decision model and an estimated potential traffic demand so that an estimated number of vehicles entering said at least one high occupancy toll lane in a next time interval will match said target traffic flow density;

generating an adjustment toll price from said feedback path based on said difference between said actual traffic flow density and said target traffic flow density with respect to said at least one high occupancy toll lane to reduce said difference, wherein said base toll price and said adjustment toll price are combined to produce a final toll price.

10. The system of claim 9 further comprising a low pass filter located in said sliding mode controller to obtain a smoother estimation of value of time and to reduce fluctuation in traffic with respect to said at least one high occupancy toll lane.

11. The system of claim 10 wherein said instructions are further configured for selecting a sliding surface and a discontinuous input to change said estimated value of time to drive dynamics of said controller towards said sliding surface wherein said sliding surface represents a desired system state.

12. The system of claim 11 wherein said instructions are further configured for permitting said discontinuous input to increase or decrease said estimated value of time upon a deviation from said sliding surface.

13. The system of claim 9 wherein said instructions are further configured for employing said estimated value of time to provide information for a study of time-varying driver choice behavior in terms of a distribution associated with said estimated value of time.

14. The system of claim 9 wherein said instructions are further configured for:

determining a driver decision model wherein a driver decides to enter said at least one high occupancy toll lane by a utility function with respect to said at least one high occupancy toll lane and at least one general purpose lane respectively based on said estimated value of time and said toll price; and

selecting said at least one high occupancy toll lane by said driver if a ratio of said utility function for said at least one high occupancy toll lane to said utility function for said at least one general purpose lane is greater than a particular threshold.

15. The system of claim 11 wherein said instructions are further configured for

obtaining an average value of time distribution signal by said low pass filter

updating an estimate of said average value of time distribution signal at each time interval;

and

utilizing said estimate of said average value of time distribution signal to determine said base toll price in order to drive said sliding surface towards zero.

16. A processor-readable medium storing code representing instructions to cause a process for sliding mode based dynamic pricing for a high occupancy toll lane, said code comprising code to:

determine an optimal target traffic flow density with respect to at least one high occupancy toll lane to achieve one or more desired performance objectives;

design a pricing controller that includes a feed-forward path and a feedback path, wherein said feed-forward path is configured with a sliding mode controller in association with a sliding mode control module to update in real-time an estimated value of time of drivers;

configure said sliding mode controller to update said estimated value of time to reduce a difference between an actual traffic flow density and a target traffic flow density with respect to said at least one high occupancy toll lane, such that said estimated value of time is updated at each time interval when said difference in said actual traffic flow density and said target traffic flow density is larger than a particular threshold;

generate a base toll price from said feed-forward path based on said estimated value of time, a driver decision model and an estimated potential traffic demand so that an estimated number of vehicles entering said at least one high occupancy toll lane in a next time interval will match said target traffic flow density; and

generate an adjustment toll price from said feedback path based on said difference between said actual traffic flow density and said target traffic flow density with respect to said at least one high occupancy toll lane to reduce said difference, wherein said base toll price and said adjustment toll price are combined to produce a final toll price.

17. The processor-readable medium of claim 16 further comprising a low pass filter in said sliding mode controller to obtain a smoother estimation of value of time and to reduce fluctuation in traffic with respect to said at least one high occupancy toll lane.

18. The processor-readable medium of claim 17 wherein said code further comprises code to select a sliding surface and a discontinuous input to change said estimated value of time to drive dynamics of said controller towards said sliding surface wherein said sliding surface represents a desired system state.

19. The processor-readable medium of claim 16 wherein said code further comprises code to employ said estimated value of time to provide information for a study of time-varying driver choice behavior in terms of a distribution associated with said estimated value of time.

20. The processor-readable medium of claim 16 wherein said code further comprises code to:

determine a driver decision model wherein a driver decides to enter said at least one high occupancy toll lane by a utility function with respect to said at least one high occupancy toll lane and at least one general purpose lane respectively based on said estimated value of time and said toll price; and

select said at least one high occupancy toll lane by said driver if a ratio of said utility function for said at least one high occupancy toll lane to said utility function for said at least one general purpose lane is greater than a particular threshold.