MacroPark

Project details

Duration

07.2014-07.2016

Sponsor

ETH Research Grant 40 14-1

Staff

Dr. M. Menendez and J. Cao

Summary

The interactions between the urban parking and traffic systems, can have both, long-term effects (i.e., parking policies can affect travel demand, and vice versa), and short-term effects (i.e., parking policies can affect traffic operations, and vice versa). While the long-term effects have attracted lots of research attention, the short-term effects have not been well researched yet. This is unfortunate, as the short-term interactions between parking and traffic can be highly significant and influential to the performance of both systems. In this study, we propose a methodology to analyze such interactions, and evaluate their effects on urban congestion.
The parking system can affect the traffic system through two processes: parking search, which can cause higher traffic density; and on-street parking maneuvers, which can directly cause additional delay. Both can lead to more congested traffic conditions, and lower travel speeds on the network. On the other side, the traffic system can also affect the parking system. Average travel speeds highly influence the arrival rate to the parking facilities, and ultimately, the level of parking usage. Here, we propose a model to evaluate these impacts at a macroscopic level. Main tools used to support the study include probability theory, macroscopic fundamental diagram, kinematic wave theory, dimensional analysis, and queuing theory.

With the proposed macroscopic model, for any given time interval, the transitions of vehicles between different parking related families (i.e., non-searching, searching, and parking) can be shown. Similarly, both the parking and traffic indicators can be updated (e.g., traffic density, average travel speed, average delay, parking occupancy, parking supply, and share of parking searchers within traffic). When the time intervals are small, the macroscopic model reflects the dynamics of both, the parking and the traffic systems. Expected outcomes from the proposed research include a methodology to measure the interactions between urban parking and traffic systems, and a short-term prediction tool for future parking and traffic conditions. Results obtained with the macroscopic methodology will be compared to those obtained with a microscopic simulation using the network of the city of Zürich, Switzerland.
The macroscopic model proposed in this study has low data requirements, but it should still provide reasonable aggregate results to make informed decisions about network management and control, as well as to assess the impact of different parking related strategies. With this approach, a better optimization scheme for the system can be developed in terms of both traffic performance and parking usage.

Publications