Parking lot allocation model considering conversion between dynamic and static traffic

Abstract

Nowadays, parking spaces are scarce resources in urban cities. Travelers often spend too much time looking for available parking spaces, which increases travel time of travelers and results in additional traffic congestion. With the innovation and application of intelligent parking technology, parking spaces can be booked in the system in advance through mobile phone, which will greatly reduce the time for drivers to cruise and search for parking spaces. Targeted at the serious waste of parking resources, traffic congestion caused by too intensive parking demand in time and space, a parking allocation model considering the ability of dynamic and static traffic conversion is established with the goal of minimizing the total travel time of the travelers. Based on the dynamic traffic distribution model, considering the constraints of capacity of the road link, parking lot entrance and the number of the parking spaces in parking lot, the dynamic and static traffic is combined by considering the parking lot connection section as a conversion link to be added into the traffic network. And the solution method based on particle swarm optimization is proposed. Experimental results on a case (Beijing Chaoyang Joy City and surrounding parking lots) show that our parking allocation model works satisfactorily by effectively reducing the travel time of travelers and increasing customer arrivals in shopping centers. From the point of view of traffic managers, the model can make the parking occupancy of all parking lots more balanced, which indicates that the model can help to better coordinate the available parking resources. In summary, the model proposed in this paper can not only divert the flow beyond the capacity of the road facilities at the connection of the parking lot, but also balance the utilization rate of the surrounding parking resources and reduce the dynamic traffic pressure, it is a proper way to develop the sustainable transportation.