Downtown parking in auto city

Abstract

This paper develops and calibrates a model of downtown parking in a city without mass transit, and applies it to investigate downtown parking policy. There is curbside and garage parking and tra¢ c congestion. Spatial competition between private parking garages determines the equilibrium garage parking fee and spacing between parking garages. Curbside parking is priced below its social opportunity cost. Cruising for parking adjusts to equalize the full prices of on-and o¤-street parking, and contributes to tra¢ c congestion. The central result is that raising curbside parking fees appears to be a very attractive policy since it generates e¢ ciency gains that may be several times as large as the increased revenues raised.

Downtown curbside parking capacity

“…Most models have assumed identical individuals, though Arnott and Rowse (2012) considered some complications arising from heterogeneity. Some models have considered an isotropic downtown area (e.g., Calthrop Arnott and Rowse, 2009. There is, of course, a substantial literature in transportation on parking, most of which considers engineering aspects, such as the design of curbside parking meters, parking garages, and parking information systems.…”

“…With P curbside parking spaces per unit area and a visit duration of l, curbside parking capacity is P=l. Third, drivers pay a curbside parking fee per unit time 7 (the 'meter rate') of f . Fourth, if there is insu¢ cient curbside parking to ration the demand with the curbside parking fee, cruising for parking occurs, and the travel time cost, which includes cruising-for-parking time cost, adjusts to clear the market.…”

“…2 Since the literature has given considerable attention to second-best policy responses to underpriced urban auto travel, the focal question of the paper is "What is the second-best level of curbside parking capacity when both urban auto travel and curbside parking are underpriced?" To address this question, this paper investigates a stylized model of downtown parking and tra¢ c congestion that builds on previous work by the authors Inci, 2006, 2010;and Arnott and Rowse, 2009). To simplify, the model assumes that individuals are identical, all travel is by car, the downtown street network is …xed and isotropic (spatially homogeneous), and public curbside (on-street) parking is supplemented by private garage (o¤-street) parking supplied elastically at unit cost, considers only the steady state, and provides an aggregative (or, in the terminology of transportation science, macroscopic) treatment of tra¢ c congestion.…”

Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing

“…Consider a system where travelling by car and searching for an on-street parking is the only available mode of transport (see for example Arnott and Rowse (2009), Geroliminis (2009), Arnott and Inci (2010), Geroliminis (2015) and Cao and Menendez (2015b)). Under high traveling and thus parking demand, the system reaches to a stable traffic state which is close to gridlock.…”

“…In case of insufficient parking capacity, for instance, cruise-for-parking flows should be treated differently than the normal running flows. Existing analysis on this subject include for instance, Arnott and Rowse (2009) and Arnott et al (2015), which took the impact of cruising into account when analyzing parking pricing policies; Martens et al (2010) examined the effect of spatial distribution of parking spots on searching-for-parking behavior; Horni et al (2013) incorporated parking choice and searching-for-parking behavior model in an agent-based framework with simplistic traffic model; He et al (2015) derived equilibrium conditions where car users compete for limited parking spaces, and investigated optimal pricing strategy to drive a system optimum. The aforementioned papers fall short in describing traffic dynamics as they assume static traffic states without dealing with the dynamics of traffic (e.g.…”