An algorithm and software for establishing heterogeneous parking prices

TL;DR

This paper introduces NPPA, an algorithm that sets spatially heterogeneous parking prices to maintain a target occupancy level, improving efficiency and economic vitality in urban parking management.

Contribution

The paper presents NPPA, a novel algorithm for establishing heterogeneous parking prices that ensure a uniform occupancy rate across diverse urban areas.

Findings

NPPA successfully maintains 90% occupancy in Bat Yam.

Heterogeneous pricing improves parking efficiency and reduces search time.

The algorithm adapts to spatial demand variations effectively.

Abstract

Parking prices in cities are uniform over large areas and do not reflect spatially heterogeneous parking supply and demand. Underpricing results in high parking occupancy in the subareas where the demand exceeds supply and long search for the vacant parking, whereas overpricing leads to low occupancy and hampered economic vitality. We present Nearest Pocket for Prices Algorithm (NPPA), a spatially explicit algorithm for establishing on-and off-street parking prices that guarantee a predetermined uniform level of occupation over the entire parking space. We apply NPPA for establishing heterogeneous parking prices that guarantee 90% parking occupancy in the Israeli city of Bat Yam.