A novel agent-based transportation model of a university campus with application to quantifying the environmental cost of parking search

This paper develops a novel agent-based transportation model of a university campus, primarily focusing on vehicle-related travel and the associated parking search process. In developing and validating the model, the study uses a wide range of data sources including: (1) a brief “trip-diary” type survey; (2) 24-h traffic counts at the entry and exit points to the campus; (3) information about the university buildings’ class room capacities and class schedules; (4) parking occupancy surveys; and (5) select intersections’ turn movement counts. The agent-based model is designed to explicitly capture trip chaining behavior, and the often-overlooked phenomenon of drivers searching for an available parking spot. The parking search process is modeled using a sequential game-theoretic, neo-additive capacity model which accounts for drivers optimistic and pessimistic attitudes regarding parking availability in their most desirable lot. The agent-based demand model is then integrated with the Transportation Analysis and Simulation System (TRANSIMS), which serves as the traffic micro-simulation engine, and with the MOVES2010 emissions model. Following the validation of the integrated model, it is used to quantify the environmental cost of the parking search process on campus. The study may be regarded as one of the few studies to integrate an agent- or activity based model of travel demand, albeit admittedly simplified, with a fine-grained transportation network, a detailed traffic micro-simulation, and a project-level emissions model. Another contribution of the study is in terms of quantifying the environmental cost, in terms of wasted fuel and increased emissions, associated with the parking search process on campus.

► We develop a novel agent-based model of a university campus.
► We integrate an activity-based model, a micro-simulator and an emissions model.
► The model incorporates a game-theoretic neo-additive capacity parking choice model.
► We validate the model against observed parking lot occupancies and traffic counts.
► We use the model to estimate the environmental cost of parking search on campus.