01622549

Component

Parking issues are critical in major cities of China nowadays. Searching and waiting for available parking spaces waste travelers’ time and induce traffic congestion on adjacent streets. Advanced parking guidance information systems are urgently needed to provide real-time parking information, predict short-term availability and assist drivers for trip planning. Many studies have been devoted to developing prediction methods for parking space availability. However, most research adopted artificial intelligence techniques instead of proposing theoretical prediction methods. The generation mechanism of parking arrivals and departures still lacks investigation. To this end, this study designed a theoretical method for parking space availability prediction. First, it defined that parking arrivals and departures are generated by past, current and future events. Next, this study developed a prediction model assuming that the probability of parking arrivals and departures obey normal distributions. Then it introduced the parking space availability prediction procedure. The proposed method was examined and analyzed with field parking data from Jinan International Airport, Shandong, China. The model prediction results were consistent with field measurements. Additionally, the analysis revealed some parking behavior characteristics. These findings could lead to implementation of parking prediction in parking guidance information systems.

This paper was sponsored by TRB committee ABJ30 Standing Committee on Urban Transportation Data and Information Systems.

01618707

17-01274

English

16p

2017

Transportation Research Board 96th Annual Meeting

Digital/other

Figures; References; Tables

Forecasting; Methodology; Parking; Parking guidance systems; Real time information

Jinan (China)

Data and Information Technology; Highways; Planning and Forecasting

Transportation Research Board Annual Meeting 2017 Paper #17-01274

TRIS, TRB, ATRI

Dec 8 2016 10:24AM