Traveling Officer Problem: Managing Car Parking Violations Efficiently Using Sensor Data
The on street parking system is an indispensable part of civic projects, as it provides travelers and shoppers with parking spaces. With the recent in ground sensors deployed throughout the Melbourne central business district (CBD) there is a significant problem on how to use the sensor data to manage parking violations and issue infringement notices efficiently in a short time window. In this paper, we use a large real world dataset with on street parking sensor data from the local city council, and establish a formulation of the traveling officer problem with a general probability based model. We propose two solutions using a spatio temporal probability model for parking officers to maximize the number of infringing cars caught with limited time cost. Using real world parking sensor data and Google Maps road network information, the experimental results show that our proposed algorithms outperform the existing patrolling routes.
IEEE Internet of Things Journal