Dependence of Parking Pricing on Land Use and Time of Day

Abstract

A key strategy of sustainable transportation, parking pricing can directly contribute to decreased greenhouse gas emissions and air pollution. This paper describes an optimal structure of parking rates in terms of parking locations and time of day. A two-level parking model based on game theory is established using parking survey data collected in Beijing in 2014. The model was estimated based on Stackelberg game and the Nash equilibrium. Using the two-level parking model, the optimal structure of parking rates for inside/outside business zones and during peak/off-peak hours was calculated. In addition, the relationship between the government (which represents the public benefit) and car users, as well as the relationships among car users in the parking system were investigated. The results indicate that equilibrium among all of the agents in the parking system can be obtained using the proposed parking rate structure. The findings provide a better understanding of parking behavior, and the two-level parking model presented in the paper can be used to determine the optimal parking rate to balance the temporal and spatial distribution of parking demand in urban areas. This research helps reduce car use and the parking-related cruising time and thus contributes to the reduction of carbon emissions and air pollution.

Planning a Park and Ride System: A Literature Review

“…Cities adopt the P&R system in order to allow more people to access traditional centers for work and shopping, while at the same time avoiding the environmental damage associated with increased highway and parking supply and more car trips [9,10]. Therefore, P&R is a modal interchange point between private vehicles and public transport users; commuters use park and ride system for the purpose of work and commercial travel [11].…”

Sustainable Mobility: A Review of Possible Actions and Policies

“…Parking pricing is, probably, the most used pricing policies in the world [179][180][181][182]. Almost all large cities in western countries, and many medium and small towns, have a parking fee on public areas, usually based on the parking time.…”

Analyses of the Imbalance of Urban Taxis’ High-Quality Customers Based on Didi Trajectory Data

“…In recent years, with the development of the global positioning system (GPS) and technology for analyzing big data, it is becoming possible to use GPS real-time positional data of taxis to study related problems. Previous research was mainly concerned with (a) using trajectory data to obtain traffic real-time status [13][14][15], passenger travel status [16,17], and personnel real-time flow [18,19] to either predict urban road congestion [20] or provide reference data for urban traffic planning; (b) exploring the spatial-temporal distribution characteristics related to traffic, such as the spatial-temporal distribution of traffic travel supply and demand [21][22][23][24][25], the spatial-temporal distribution of taxis and passengers [26], the spatial-temporal distribution of the stream of people and traffic flow [27][28][29][30], and occupational and residential traffic [31], by studying the statistical rules of various elements of transportation and providing either theoretical or technical support for traffic management; and (c) the reality of taking advantage of trajectory data to study the efficiency of taxi operation and drivers' service profit margins. Examples are exploring the balance between urban taxi supply and passenger travel to evaluate the operational efficiency based on the capacity utilization data and vacancy data of taxis [32,33], studying the search behavior of taxis in vacancy and simulating the effects of supply and demand balance for taxis [34], establishing taxi and ride-hailing service models to quantify drivers' service profit margins to improve taxi drivers' revenue [5], and constructing a spatial-temporal trajectory model of the balanced distribution with load to optimize the information matching between passengers and drivers and improve the operational efficiency of taxis [35][36][37].…”