In this paper we formulate a dynamic mixed integer program for optimally zoning curbside parking spaces subject to transportation policy-inspired constraints and regularization terms. First, we illustrate how given some objective of curb zoning valuation as a function of zone type (e.g., paid parking or bus stop), dynamically rezoning involves unrolling this optimization program over a fixed time horizon. Second, we implement two different solution methods that optimize for a given curb zoning value function. In the first method, we solve long horizon dynamic zoning problems via approximate dynamic programming. In the second method, we employ Dantzig-Wolfe decomposition to break-up the mixed-integer program into a master problem and several sub-problems that we solve in parallel; this decomposition accelerates the MIP solver considerably. We present simulation results and comparisons of the different employed techniques on vehicle arrival-rate data obtained for a neighborhood in downtown Seattle, Washington, USA.
Optimal, centralized dynamic curbside parking space zoning
2022-10-08
1584447 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Elsevier | 2013
|Online Contents | 2013
|Parking Reservation for Managing Downtown Curbside Parking
Transportation Research Record | 2015
|Parking Reservation for Managing Downtown Curbside Parking
Online Contents | 2015
|Curbside Parking Monitoring With Roadside LiDAR
Transportation Research Record | 2023
|