Abstract

Classical parking functions are defined as the parking preferences for $n$ cars driving (from west to east) down a one-way street containing parking spaces labeled from $1$ to $n$ (from west to east). Cars drive down the street toward their preferred spot and park there if the spot is available. Otherwise, the car continues driving down the street and takes the first available parking space, if such a space exists. If all cars can park using this parking rule, we call the $n$-tuple containing the cars' parking preferences a parking function. 
 In this paper, we introduce a generalization of the parking rule allowing cars whose preferred space is taken to first proceed up to $k$ spaces west of their preferred spot to park before proceeding east if all of those $k$ spaces are occupied. We call parking preferences which allow all cars to park under this new parking rule $k$-Naples parking functions of length $n$. This generalization gives a natural interpolation between classical parking functions, the case when $k=0$, and all $n$-tuples of positive integers $1$ to $n$, the case when $k\geq n-1$. Our main result provides a recursive formula for counting $k$-Naples parking functions of length $n$. We also give a characterization for the $k=1$ case by introducing a new function that maps $1$-Naples parking functions to classical parking functions, i.e. $0$-Naples parking functions. Lastly, we present a bijection between $k$-Naples parking functions of length $n$ whose entries are in weakly decreasing order and a family of signature Dyck paths.

Highlights

  • Parking functions were introduced independently by Ronald Pyke and by Alan Konheim and Benjamin Weiss in relation to hashing problems [5, 6]

  • Consider n parking spaces on a one-way street arranged in a line numbered 1 to n from west to east

  • Suppose there are n cars, denoted c1, c2, . . . , cn, that drive in order down this one-way street

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Summary

Introduction

Parking functions were introduced independently by Ronald Pyke and by Alan Konheim and Benjamin Weiss in relation to hashing problems [5, 6]. The case where there are more parking spots than cars is considered in [5, Lemma 2] and counted by (n+1−m)(n+1)m−1, where m is the number of cars and n is the number of spaces in the lot, with n m Another generalization of parking functions given in [8], known as x-parking functions, are defined by generalizing the necessary and sufficient condition so that given α ∈ P Pn and a vector x = Ci continues east and parks in the first unoccupied spot If under this new parking rule the parking preference α allows all cars to park, we call α a Naples parking function. If under the parking preference α all cars can pMainRecursionark using this new parking rule, we say that α is a k-Naples parking function of length n and we denote this set by P Fn,k.

Background and preliminaries
Counting Naples Parking Functions Recursively
Characterization of Naples Parking Functions
Connections to Decreasing Lattice Paths
Rearrangements of k-Naples parking functions
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