| Summary |
With the increase in economic behavior the private vehicles continue to grow in Taiwan. However, it is not easy to increase parking supply especially in metropolitan area. Therefore, people often faced with the problem of imbalance between parking supply and demand. When there is a parking supply and demand problem it needs to be improved by intelligent traffic management method. Great roadside parking management can avoid traffic congestion and fuel consumption.
“On-street parking fee" is a policy implemented by the government to charge and manage the use of public goods. However, the current charging method mostly adopts a single and low-cost method. Therefore, it is common for parking spaces to be occupied for a long time and the turnover rate of parking spaces is low. The parking environment makes those who want to park continue to detour in the traffic. Introduce a differential pricing strategy to reduce rates during off-peak hours or where no one parks and increase rates during peak hours and areas with low turnover rates. It can use price factors to guide people to choose parking locations, so that parking grids can be used more evenly.
Tainan City is the city with the most complete smart parking services among the major cities in Taiwan. Therefore, Tainan City was chosen as the research location to showcase innovative services. The main idea is to improve the service content and efficiency of the existing smart parking APP. Draw a service blueprint and innovate smart roadside parking guidance services by means of differential pricing and demand forecasting. Use the real-time parking data to construct a demand forecast model and issue questionnaires to understand consumers' preferences for differential pricing. Construct a smart parking service system based on the above concepts and add a member management system to compensate for service failures in order to become a service platform that meets the needs and preferences of consumers. In addition, the benefits of this service to urban road traffic are estimated through traffic simulation. This study explores the potential of this important subsystem of services, with the hope that it will enable the efficient use of public parking resources while achieving the policy goal of improving urban traffic management. |
