4.7 Article

Pricing of parking games with atomic players

Journal

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trb.2014.12.003

Keywords

Atomic parking game; Equilibrium; System optimum; Pricing

Funding

  1. U.S. National Science Foundation [CMMI-1362631, CNS-1239364]
  2. National Natural Science Foundation of China [71228101]
  3. Directorate For Engineering
  4. Div Of Civil, Mechanical, & Manufact Inn [1362631] Funding Source: National Science Foundation
  5. Division Of Computer and Network Systems
  6. Direct For Computer & Info Scie & Enginr [1239364] Funding Source: National Science Foundation

Ask authors/readers for more resources

This paper considers a parking competition game where a finite number of vehicles from different origins compete for the same number of parking spaces located at various places in a downtown area to minimize their own parking costs. If one vehicle reaches a desired vacant parking space before another vehicle, it will occupy the space and the other vehicle would have to search elsewhere. We first present a system of nonlinear equations to describe the equilibrium assignment of parking spaces to vehicles, and then discuss optimal pricing schemes that steer such parking competition to a system optimum assignment of parking spaces. These schemes are characterized by a union of polyhedrons. Given that the equilibrium state of parking competition is not unique, we further introduce a valid price vector to ensure that the parking competition outcome will always be system optimum. A sufficient condition is provided for the existence of such a valid price vector. Lastly, we seek for a robust price vector that yields the best worst-case outcome of the parking competition. (C) 2014 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available