Computational Modelling Group

Simulation of Parking Choice Behaviour

14th June 2010
20th September 2010
Research Team
James Snowdon
Ben Waterson, Hans Fangohr

A driver's choice of parking space is a complex decision dependent on the observed state of the ever changing network combined with personal preference and experience. We aim to explore this behaviour through simulation modelling.

The task of searching for a parking location can be likened to a smaller scale representation of the decision making processes carried out by a driver undergoing any full journey. Drivers arriving near to their destination must consider the route leading to optimum utility of (to their knowledge) available parking stock, weighing up the costs of continuing the search for a 'more desirable' space against costs incurred in terms of time and fuel consumption. The decision making process giving rise to this choice of search strategy has been modelled using agent based simulation models which have previously only considered the immediate environment local to the driver, however there is scope to further extend these models to consider the effects of prior knowledge of the system, 'habit', and the evolution of behaviour over time as a driver learns about and familiarises themselves with the system.

With pressures on urban land use growing, leading to a likely decline in parking stock coupled with a growing population, it would be expected that a significant proportion of traffic in inner cities is comprised of drivers trying to find a place to park. Understanding the search process employed by drivers can aide decision makers in implementing an effective parking management strategy.

This project will therefore consider how psychological models of individual parking search behaviours can be combined into a simulation of parking search behaviour, and hence allow assessment of the impact on searching traffic of different supply/ demand ratios, different driver population characteristics and different charging regimes. This will be achieved through theoretical analysis leading to simulation model development calibrated by a study of a number of case study sites around Southampton by means of monitoring the recorded actions of drivers, discussion and questionnaire based surveys with users.

Existing literature and agent based simulation models will aid the project's progress, but the focus on applying more complex psychological frameworks to focus on the effect of prior knowledge and the act of network discovery appears to be novel.


Socio-technological System simulation: Transport

Algorithms and computational methods: Agents, Evolutionary Algorithms

Transdisciplinary tags: Complex Systems, Software Engineering