Improving Utilization and Customer Satisfaction of Parking Space with M2M Communications

• Main Authors: Chen, Hao-Ru, 陳灝儒
• Other Authors: Lin, Fu-Chun
• Format: Others
• Language: en_US
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/78456914993362012826

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 103 === The demand for parking space has increased dramatically due to the increase of vehicles in the world. At the same time, it is hard to create new parking spaces because of the continual growth of population density. Although public transit systems have advanced as an economical and ecofriendly alternative to cars, people prefer to drive the car to their destination because it takes less time and is more flexible for many trips. As a result, the significant shortage of parking spaces in cities creates a challenging problem for both drivers and parking space operators. For drivers, problems include searching for an available parking space quickly, locating the space that is the closest to the destination, and afterwards finding the car without pain in a big parking garage. For operators, problems include identifying all parameters of parking space management and developing the best management policy to satisfy needs of different customers while maintaining a high utilization rate. In this research, we focus on problems of operators. We develop a method of simulation to study these problems. We implement the parking simulation system by using SimPy, a process-based discrete-event simulation framework based on standard Python. The operator can use our method to evaluate different parking policies and find out the best policy. Parking policy is a set of rules established by operators. Drivers are required to obey these rules when they use the parking lot. Parking policy is created by defining different types of parking spaces and prices. The operator also can use our method to estimate the impact of Smart Parking System (SPS) on parking space management. An SPS not only tracks the number and locations of available parking spaces in an area but also utilizes Machine-to-Machine communications (M2M) to provide drivers useful information about the status of a parking area. We create three sets of experiments to study these problems and use the satisfaction rate and the occupancy rate to evaluate the performance. Based on the results obtained from our simulation, we are able to identify the best policy among all alternatives which achieves the highest satisfaction rate under the constraint of maintaining certain occupancy rate. Furthermore, our simulation shows that the SPS can improve the satisfaction rate regardless scenarios under different assumptions.