Parking Pricing for a Sustainable Transport System

Abstract

The purpose of this study has been the develop of a model for designing an efficient parking pricing policy. The aim is an\ud intelligent control and management system of parking pricing integrated with a redefinition of the circulation scheme for a\ud limited traffic zone in the Central Business District (CBD) of Palermo.\ud The transport demand over the entire area of the town has been studied in order to design various parking pricing scenarios with\ud the application of an additional cost on parking inside the selected area of the CBD. This area attracts most of the private\ud vehicular traffic and it is characterized by university faculties, schools, hospitals, offices and commercial areas.\ud The optimal hourly toll is defined by an iterative maximization process of an objective function. This objective function is\ud subject to the following constraint: the percentage of available parking in the various parking zones has to remain major of the\ud 30%. In this way, the users who need to park close to their final destination can easily find parking. Otherwise it is possible to\ud leave the private car in a “park and ride” area and taking a shuttle bus directed towards the zones of the CBD.\ud A basic principle of this pricing policy is the re-use of revenues for two purposes: to design a shuttle bus service that connects the\ud various “park and ride” areas to the CBD and to improve the local public transport service on the OD pairs that show high travel\ud demand. At the same time it is necessary to eliminate the stop and go flow in cordon roads to increase the capacity and avoid\ud congestion in these critical links.\ud The method shows that in a very simple, and relatively fast, way is possible to get a proposal for the modification of the parking\ud pricing scheme that makes the city center no longer stifled by private car traffic

A Novel Scheme to Relieve Parking Pressure at Tourist Attractions on Holidays

“…The coefficient associated with Scenario 1 (0. 20) indicates that tourists are likely to parking at Liulang Natatorim and willing to pay ¥1.25 (0.2/´0.16) more for parking if they can walk along green shaded trails to the destinations. The coefficient associated with Scenario 3 (0.62) indicates that tourists prefer to park at Huangdichuan Wharf and would like to spend ¥3.65 (0.62/´0.17) more for parking if the water way from the parking lot to the destinations with great scenery.…”

“…In addition, the alternative transportation may use various scenic roadways and routs. Many researches also try to deal with parking demands from the economic view, which expect to control parking demand by manipulating the relationship of parking price and parking provision [16][17][18][19][20]. For example, Shoup optimized parking prices to reduce cruising time for parking space [21][22][23].…”

Simulation, Optimization, and Machine Learning in Sustainable Transportation Systems: Models and Applications

“…They used a combination of neural networks and logit regression to identify the factors that influence citizens' decision about vehicle ownership, including: existence of an efficient public transportation system, age, gender, income and job sector, taxi services, etc. In the context of the Palermo city, Migliore et al [100] propose a demand-based optimization model, and a solving heuristic, for efficient parking pricing. The model aims at balancing the different transportation modes in the city, from private cars to public buses.…”

Sistem Pembayaran Parkir Menggunakan NEAR FIELD COMMUNICATION Berbasis ANDROID dan Teknologi INTERNET OF THINGS

“…Masalah kesalahan penghitungan biaya parkir secara manual sering terjadi, disamping lamanya waktu yang dibutuhkan untuk antri saat melakukan pembayaran [2]. Dari segi pengelola parkir, biaya yang dikeluarkan untuk melakukan pengontrolan biaya parkir menjadi lebih besar ketika dilakukan secara manual oleh petugas parkir [3]. Keamanan kendaraan juga menjadi masalah dalam sistem pengolaan parkir, sehingga banyak orang bersedia untuk menghabiskan dana yang lebih banyak untuk memastikan kendaraan mereka aman [2].…”